Optional Syntax Elements for TD_WordEmbeddings - Teradata VantageCloud Lake
Lake - Analyze Your Data with ClearScape Analytics™
Deployment
VantageCloud
Edition
Lake
Product
Teradata VantageCloud Lake
Release Number
Published
February 2025
ft:locale
en-US
ft:lastEdition
2026-02-20
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tcl1683670667798.ditamap
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pny1626732985837.ditaval
dita:id
tcl1683670667798
Analyze Your Data with ClearScape Analytics
Vantage Analytics Library
Bring Your Own Model
In-Database Analytic Functions
In-Database Analytic Function Categories
Data Cleaning Functions
Data Exploration Functions
Feature Engineering Transform Functions
Feature Engineering Utility Functions
Model Training Functions
Model Scoring Functions
Model Evaluation Functions
Text Analytic Functions
Hypothesis Testing Functions
Association Analysis Functions
Path and Pattern Analysis Functions
Usage Notes
How to Read Syntax
Input Table Rows Redistribution
Function Syntax Descriptions
Size of the Query
AMP Configuration Impact on Function Execution
Limitations When Using PARTITION BY
Functions Ignore Disallowed Syntax Elements
Input Table Schemas
Function Names with and without TD Prefix
Accumulated Columns Impact on Function Performance
Datatype Change in Accumulated Columns
View Online Help for In-Database Analytic Functions
BC/BCE Timestamps
Workload Management Configuration for In-Database Analytic Functions
Avoid Deadlocks Using Volatile Tables
Non-Deterministic Behavior
Maximum Number of Columns in a Database Table
Spool Space Exhaustion for Large Partitions at High Concurrency
Recommendations for Using Analytic Functions
Data Cleaning Functions
Pack
Pack Syntax
Required Syntax Elements for Pack
Optional Syntax Elements for Pack
Pack Input
Pack Output
Examples: How to Use Pack
Pack Examples Input
Example: Default Options
Example: Nondefault Options
StringSimilarity
StringSimilarity Syntax
StringSimilarity Syntax Elements
StringSimilarity Input
StringSimilarity Output
Examples: How to Use StringSimilarity
StringSimilarity with Specified Column Names
StringSimilarity with Specified Column Ranges
TD_ConvertTo
TD_ConvertTo Syntax
Required Syntax Elements for TD_ConvertTo
Optional Syntax Elements for TD_ConvertTo
TD_ConvertTo Input
TD_ConvertTo Output
TD_ConvertTo Usage Notes
Example: How to Use TD_ConvertTo
TD_GetFutileColumns
TD_GetFutileColumns Syntax
Required Syntax Elements for TD_GetFutileColumns
Optional Syntax Elements for TD_GetFutileColumns
TD_GetFutileColumns Input
TD_GetFutileColumns Output
Example: How to Use TD_GetFutileColumns
TD_GetRowsWithoutMissingValues
TD_GetRowsWithoutMissingValues Syntax
Required Syntax Elements for TD_GetRowsWithoutMissingValues
TD_GetRowsWithoutMissingValues Input
TD_GetRowsWithoutMissingValues Output
Example: How to Use TD_GetRowsWithoutMissingValues
TD_OutlierFilterFit
TD_OutlierFilterFit Syntax
Required Syntax Element for TD_OutlierFilterFit
Optional Syntax Elements for TD_OutlierFilterFit
TD_OutlierFilterFit Input
TD_OutlierFilterFit Output
Example: Using TD_OutlierFilterFit with Percentile Method
TD_OutlierFilterTransform
TD_OutlierFilterTransform Syntax
Required Syntax Elements for TD_OutlierFilterTransform
Optional Syntax Elements for TD_OutlierFilterTransform
TD_OutlierFilterTransform Input
TD_OutlierFilterTransform Output
Example: How to Use TD_OutlierFilterTransform
TD_SimpleImputeFit
TD_SimpleImputeFit Syntax
Required Syntax Elements for TD_SimpleImputeFit
Optional Syntax Elements for TD_SimpleImputeFit
TD_SimpleImputeFit Input
TD_SimpleImputeFit Output
Example: How to Use TD_SimpleImputeFit
TD_SimpleImputeTransform
TD_SimpleImputeTransform Syntax
Required Syntax Elements for TD_SimpleImputeTransform
Optional Syntax Elements for TD_SimpleImputeTransform
TD_SimpleImputeTransform Input
TD_SimpleImputeTransform Output
Example: How to Use TD_SimpleImputeTransform
Unpack
Unpack Syntax
Unpack Syntax Elements
Unpack Input
Unpack Output
Examples: How to Use Unpack
Example: Delimiter Separates Virtual Columns
Example: No Delimiter Separates Virtual Columns
Example: More Input Columns than Output Columns
Example: Input Columns with Trailing Special Characters
Data Exploration Functions
MovingAverage
Simple Moving Average
Weighted Moving Average
Exponential Moving Average
Modified Moving Average
Cumulative Moving Average
Triangular Moving Average
MovingAverage Syntax
Required Syntax Elements for MovingAverage
Optional Syntax Elements for MovingAverage
MovingAverage Input
MovingAverage Output
Examples: How to Use MovingAverage
MovingAverage Examples Input
Example: Simple Moving Average
Example: Weighted Moving Average
Example: Exponential Moving Average
Example: Modified Moving Average
Example: Cumulative Moving Average
Example: Triangular Moving Average
TD_CategoricalSummary
TD_CategoricalSummary Syntax
Required Syntax Elements for TD_CategoricalSummary
Optional Syntax Elements for TD_CategoricalSummary
TD_CategoricalSummary Input
TD_CategoricalSummary Output
Example: How to Use TD_CategoricalSummary
TD_ColumnSummary
TD_ColumnSummary Syntax
Required Syntax Elements for TD_ColumnSummary
Optional Syntax Elements for TD_ColumnSummary
TD_ColumnSummary Input
TD_ColumnSummary Output
Example: How to Use TD_ColumnSummary
TD_GetRowsWithMissingValues
TD_GetRowsWithMissingValues Syntax
Required Syntax Elements for TD_GetRowsWithMissingValues
Optional Syntax Elements for TD_GetRowsWithMissingValues
TD_GetRowsWithMissingValues Input
TD_GetRowsWithMissingValues Output
Example: Using TD_GetRowsWithMissingValues to Find NULL Values
TD_Histogram
TD_Histogram Syntax
Required Syntax Elements for TD_Histogram
Optional Syntax Elements for TD_Histogram
TD_Histogram Input
TD_Histogram Output
Examples: How to Use TD_Histogram
TD_QQNorm
TD_QQNorm Syntax
Required Syntax Elements for TD_QQNorm
Optional Syntax Elements for TD_QQNorm
TD_QQNorm Input
TD_QQNorm Output
Example: How to Use TD_QQNorm
TD_UnivariateStatistics
TD_UnivariateStatistics Syntax
TD_UnivariateStatistics Syntax Elements
TD_UnivariateStatistics Input
TD_UnivariateStatistics Output
Example: Using TD_UnivariateStatistics to Determine Mean, Median, and Mode
TD_WhichMax
TD_WhichMax Syntax
Required Syntax Elements for TD_WhichMax
Optional Syntax Elements for TD_WhichMax
TD_WhichMax Input
TD_WhichMax Output
TD_WhichMax Example
TD_WhichMin
TD_WhichMin Syntax
Required Syntax Elements for TD_WhichMin
Optional Syntax Elements for TD_WhichMin
TD_WhichMin Input
TD_WhichMin Output
TD_WhichMin Example
Feature Engineering Transform Functions
Antiselect
Antiselect Syntax
Antiselect Syntax Elements
Antiselect Input
Antiselect Output
Antiselect Examples
Antiselect Example: No Column Ranges
Antiselect Example: Column Range
TD_BinCodeFit
TD_BinCodeFit Syntax
Required Syntax Elements for TD_BinCodeFit
Optional Syntax Elements for TD_BinCodeFit
TD_BinCodeFit Input
TD_BinCodeFit Output
Example: How To Use TD_BinCodeFit
TD_BinCodeTransform
TD_BinCodeTransform Syntax
Required Syntax Elements for TD_BinCodeTransform
Optional Syntax Elements for TD_BinCodeTransform
TD_BinCodeTransform Input
TD_BinCodeTransform Output
TD_BinCodeTransform Usage Notes
Example: How to Use TD_BinCodeTransform
TD_ColumnTransformer
TD_ColumnTransformer Syntax
TD_ColumnTransformer Syntax Elements
TD_ColumnTransformer Input
TD_ColumnTransformer Output
TD_ColumnTransformer Example
TD_FunctionFit
TD_FunctionFit Syntax
TD_FunctionFit Input
TD_FunctionFit Output
TD_FunctionFit Example
TD_FunctionTransform
TD_FunctionTransform Syntax
TD_FunctionTransform Syntax Elements
TD_FunctionTransform Input
TD_FunctionTransform Output
TD_FunctionTransform Example
TD_NonLinearCombineFit
TD_NonLinearCombineFit Syntax
Required Syntax Elements for TD_NonLinearCombineFit
Optional Syntax Elements for TD_NonLinearCombineFit
TD_NonLinearCombineFit Input
TD_NonLinearCombineFit Output
Example: How to Use TD_NonLinearCombineFit
TD_NonLinearCombineTransform
TD_NonLinearCombineTransform Syntax
Required Syntax Elements for TD_NonLinearCombineTransform
Optional Syntax Elements for TD_NonLinearCombineTransform
TD_NonLinearCombineTransform Input
TD_NonLinearCombineTransform Output
Example: How to Use TD_NonLinearCombineTransform
TD_OneHotEncodingFit
TD_OneHotEncodingFit Syntax
Required Syntax Elements for TD_OneHotEncodingFit
Optional Syntax Elements for TD_OneHotEncodingFit
TD_OneHotEncodingFit Input
TD_OneHotEncodingFit Output
TD_OneHotEncodingFit Usage Notes
Example: How to Use TD_OneHotEncodingFit
TD_OneHotEncodingTransform
TD_OneHotEncodingTransform Syntax
Required Syntax Elements for TD_OneHotEncodingTransform
Optional Syntax Elements for TD_OneHotEncodingTransform
TD_OneHotEncodingTransform Input
TD_OneHotEncodingTransform Output
Example: How to Use TD_OneHotEncodingTransform
TD_OrdinalEncodingFit
TD_OrdinalEncodingFit Syntax
Required Syntax Elements for TD_OrdinalEncodingFit
Optional Syntax Elements for TD_OrdinalEncodingFit
TD_OrdinalEncodingFit Input
TD_OrdinalEncodingFit Output
Example: How to Use TD_OrdinalEncodingFit
TD_OrdinalEncodingTransform
TD_OrdinalEncodingTransform Syntax
Required Syntax Elements for TD_OrdinalEncodingTransform
Optional Syntax Elements for TD_OrdinalEncodingTransform
TD_OrdinalEncodingTransform Input
TD_OrdinalEncodingTransform Output
Example: How to Use TD_OrdinalEncodingTransform
TD_Pivoting
TD_Pivoting Syntax
Required Syntax Elements for TD_Pivoting
Optional Syntax Elements for TD_Pivoting
TD_Pivoting Input
TD_Pivoting Output
Example: How to Use TD_Pivoting
RowsPerPartition
PivotColumn
Aggregation with PivotColumn
Aggregation Only
TD_PolynomialFeaturesFit
TD_PolynomialFeaturesFit Syntax
Required Syntax Elements for TD_PolynomialFeaturesFit
TD_PolynomialFeaturesFit Input
TD_PolynomialFeaturesFit Output
Example: How to Use TD_PolynomialFeaturesFit
TD_PolynomialFeaturesTransform
TD_PolynomialFeaturesTransform Syntax
TD_PolynomialFeaturesTransform Syntax Elements
TD_PolynomialFeaturesTransform Input
TD_PolynomialFeaturesTransform Output
Example: How to Use TD_PolynomialFeaturesTransform
TD_RandomProjectionFit
TD_RandomProjectionFit Syntax
TD_RandomProjectionFit Syntax Elements
TD_RandomProjectionFit Input
TD_RandomProjectionFit Output
TD_RandomProjectionFit Example
TD_RandomProjectionMinComponents
TD_RandomProjectionMinComponents Syntax
TD_RandomProjectionMinComponents Syntax Elements
TD_RandomProjectionMinComponents Input
TD_RandomProjectionMinComponents Output
TD_RandomProjectionMinComponents Example
TD_RandomProjectionTransform
TD_RandomProjectionTransform Syntax
TD_RandomProjectionTransform Syntax Elements
TD_RandomProjectionTransform Input
TD_RandomProjectionTransform Output
TD_RandomProjectionTransform Example
TD_RowNormalizeFit
TD_RowNormalizeFit Syntax
Required Syntax Elements for TD_RowNormalizeFit
Optional Syntax Elements for TD_RowNormalizeFit
TD_RowNormalizeFit Input
TD_RowNormalizeFit Output
Example: How to Use TD_RowNormalizeFit
TD_RowNormalizeTransform
TD_RowNormalizeTransform Syntax
Required Syntax Elements for TD_RowNormalizeTransform
Optional Syntax Elements for TD_RowNormalizeTransform
TD_RowNormalizeTransform Input
TD_RowNormalizeTransform Output
Example: How to Use TD_RowNormalizeTransform
TD_ScaleFit
TD_ScaleFit Syntax
Required Syntax Elements for TD_ScaleFit
Optional Syntax Elements for TD_ScaleFit
TD_ScaleFit Input
TD_ScaleFit Output
Examples: How to Use TD_ScaleFit
Dense Input
Sparse Input without Partition
Sparse Input with Partition
TD_ScaleTransform
TD_ScaleTransform Syntax
Required Syntax Elements for TD_ScaleTransform
Optional Syntax Elements for TD_ScaleTransform
TD_ScaleTransform Input
TD_ScaleTransform Output
Examples: How to Use TD_ScaleTransform
Dense Input
Sparse Input without Partition
Sparse Input with Partition
TD_SMOTE
TD_SMOTE Syntax
Required Syntax Elements for TD_SMOTE
Optional Syntax Elements for TD_SMOTE
TD_SMOTE Input
TD_SMOTE Output
TD_SMOTE Usage Notes
Examples: How to Use TD_SMOTE
Using SamplingStrategy with smote, adasyn or borderline Values
Using SamplingStrategy with smotenc Values
TD_TargetEncodingFit
TD_TargetEncodingFit Syntax
TD_TargetEncodingFit Syntax Elements
TD_TargetEncodingFit Input
TD_TargetEncodingFit Output
TD_TargetEncodingFit Usage Notes
TD_TargetEncodingFit Examples
TD_TargetEncodingTransform
TD_TargetEncodingTransform Syntax
TD_TargetEncodingTransform Syntax Elements
TD_TargetEncodingTransform Input
TD_TargetEncodingTransform Output
TD_TargetEncodingTransform Usage Notes
TD_TargetEncodingTransform Examples
TD_Unpivoting
TD_Unpivoting Syntax
Required Syntax Elements for TD_Unpivoting
Optional Syntax Elements for TD_Unpivoting
TD_Unpivoting Input
TD_Unpivoting Output
TD_Unpivoting Usage Notes
Example: How to Use TD_Unpivoting
Feature Engineering Utility Functions
TD_FillRowID
TD_FillRowID Syntax
Required Syntax Elements for TD_FillRowID
Optional Syntax Elements for TD_FillRowID
TD_FillRowID Input
TD_FillRowID Output
Example: Using TD_FillRowID to Generate Row Identifiers
TD_NumApply
TD_NumApply Syntax
Required Syntax Elements for TD_NumApply
TD_NumApply Input
TD_NumApply Output
Example: How to Use TD_NumApply
TD_RoundColumns
TD_RoundColumns Syntax
Required Syntax Elements for TD_RoundColumns
Optional Syntax Elements for TD_RoundColumns
TD_RoundColumns Input
TD_RoundColumns Output
Example: How to Use TD_RoundColumns
TD_RoundColumns Column Examples
TD_StrApply
TD_StrApply Syntax
TD_StrApply Syntax Elements
TD_StrApply Input
TD_StrApply Output
Example: How to Use TD_StrApply
Model Training Functions
TD_DecisionForest
TD_DecisionForest Syntax
Required Syntax Elements for TD_DecisionForest
Optional Syntax Elements for TD_DecisionForest
TD_DecisionForest Input
TD_DecisionForest Output
TD_DecisionForest Usage Notes
TD_DecisionForest Examples
TD_GLM
TD_GLM Syntax
Required Syntax Elements for TD_GLM
Optional TD_GLM Syntax Elements
TD_GLM Input
TD_GLM Output
Examples: How to Use TD_GLM
TD_HNSW
TD_HNSW Syntax
Required Syntax Elements for TD_HNSW
Optional Syntax Elements for TD_HNSW
TD_HNSW Input
TD_HNSW Output
Examples: How to Use TD_HNSW
TD_KMeans
TD_KMeans Syntax
Required Syntax Elements for TD_KMeans
Optional Syntax Elements for TD_KMeans
TD_KMeans Input
TD_KMeans Output
TD_KMeans Usage Notes
Examples: How to Use TD_KMeans
InitialCentroids Examples Using TD_KMeans
Vector Example Using TD_KMeans
Vector32 Example Using TD_KMeans
Cosine Similarity for Distance Measure Example (Vector) using TD_KMeans
Cosine similarity for distance measure Example (Vector32) using TD_KMeans
TD_KNN
TD_KNN Syntax
TD_KNN Syntax Elements
TD_KNN Input
TD_KNN Output
Examples: How to Use TD_KNN
Example: Using TD_KNN To Predict Weight Based on Height and Age
Example: Using TD_KNN with Classification
Example: Using TD_KNN with Neighbors
TD_NaiveBayes
TD_NaiveBayes Syntax
Required Syntax Elements for TD_NaiveBayes
Optional Syntax Elements for TD_NaiveBayes
TD_NaiveBayes Input
TD_NaiveBayes Output
Example: How to Use TD_NaiveBayes
TD_OneClassSVM
TD_OneClassSVM Syntax
Required Syntax Elements for TD_OneClassSVM
Optional Syntax Elements for TD_OneClassSVM
TD_OneClassSVM Input
TD_OneClassSVM Output
TD_OneClassSVM Usage Notes
Example: How to Use TD_OneClassSVM
TD_SVM
TD_SVM Syntax
Required Syntax Elements for TD_SVM
Optional Syntax Elements for TD_SVM
TD_SVM Input
TD_SVM Output
Examples: How to Use TD_SVM
TD_VectorDistance
TD_VectorDistance Syntax
Required Syntax Elements for TD_VectorDistance
Optional Syntax Elements for TD_VectorDistance
TD_VectorDistance Input
TD_VectorDistance Output
TD_VectorDistance Usage Notes
Examples: Using TD_VectorDistance
Euclidean, Manhattan, and Cosine Examples Using TD_VectorDistance
Vector Example Using TD_VectorDistance
Vector32 Example Using TD_VectorDistance
TD_XGBoost
TD_XGBoost Syntax
Required Syntax Elements for TD_XGBoost
Optional Syntax Elements for TD_XGBoost
TD_XGBoost Input
TD_XGBoost Output
Examples: How to Use TD_XGBoost
TD_XGBoost for Classification
TD_XGBoost for Regression
TD_XGBoost for JSON Tree Model String
TD_XGBoost using Data Redistribution
Model Scoring Functions
TD_DecisionForestPredict
TD_DecisionForestPredict Syntax
Required Syntax Elements for TD_DecisionForestPredict
Optional Syntax Elements for TD_DecisionForestPredict
TD_DecisionForestPredict Input
TD_DecisionForestPredict Output
TD_DecisionForestPredict Usage Notes
Example: How to Use TD_DecisionForestPredict
TD_GLMPredict
TD_GLMPredict Syntax
Required Syntax Elements for TD_GLMPredict
Optional Syntax Elements for TD_GLMPredict
TD_GLMPredict Input
TD_GLMPredict Output
Examples: How to Use TD_GLMPredict
TD_HNSWPredict
TD_HNSWPredict Syntax
Required Syntax Elements for TD_HNSWPredict
Optional Syntax Elements for TD_HNSWPredict
TD_HNSWPredict Input
TD_HNSWPredict Output
Example: How to Use TD_HNSWPredict
TD_KMeansPredict
TD_KMeansPredict Syntax
Required Syntax Elements for TD_KMeansPredict
Optional Syntax Elements for TD_KMeansPredict
TD_KMeansPredict Input
TD_KMeansPredict Output
Examples: How to Use TD_KMeansPredict
k-means Algorithm Examples Using TD_KMeansPredict
Cluster Centroid Examples Using TD_KMeansPredict
Vector Example Using TD_KMeansPredict
Vector32 Examples Using TD_KMeansPredict
TD_NaiveBayesPredict
TD_NaiveBayesPredict Syntax
Required Syntax Elements for TD_NaiveBayesPredict
Optional Syntax Elements for TD_NaiveBayesPredict
TD_NaiveBayesPredict Input
TD_NaiveBayesPredict Output
Example: How to Use TD_NaiveBayesPredict
TD_OneClassSVMPredict
TD_OneClassSVMPredict Syntax
Required Syntax Elements for TD_OneClassSVMPredict
Optional Syntax Elements for TD_OneClassSVMPredict
TD_OneClassSVMPredict Input
TD_OneClassSVMPredict Output
Example: How to Use TD_OneClassSVMPredict
TD_SVMPredict
TD_SVMPredict Syntax
Required Syntax Elements for TD_SVMPredict
Optional Syntax Elements for TD_SVMPredict
TD_SVMPredict Input
TD_SVMPredict Output
TD_SVMPredict Usage Notes
Examples: How to Use TD_SVMPredict
TD_XGBoostPredict
TD_XGBoostPredict Syntax
Required Syntax Elements for TD_XGBoostPredict
Optional Syntax Elements for TD_XGBoostPredict
TD_XGBoostPredict Input
TD_XGBoostPredict Output
Examples: How to Use TD_XGBoostPredict
XGBoostPredict for Classification
XGBoostPredict for Regression
Model Evaluation Functions
TD_ClassificationEvaluator
TD_ClassificationEvaluator Syntax
Required Syntax Elements for TD_ClassificationEvaluator
Optional Syntax Elements for TD_ClassificationEvaluator
TD_ClassificationEvaluator Input
TD_ClassificationEvaluator Output
TD_ClassificationEvaluator Usage Notes
Example: How to Use TD_ClassificationEvaluator
TD_HNSWSummary
TD_HNSWSummary Syntax
Required Syntax Elements for TD_HNSWSummary
Optional Syntax Elements for TD_HNSWSummary
TD_HNSWSummary Input
TD_HNSWSummary Output
Example: How to Use TD_HNSWSummary
TD_RegressionEvaluator
TD_RegressionEvaluator Syntax
TD_RegressionEvaluator Syntax Elements
TD_RegressionEvaluator Input
TD_RegressionEvaluator Output
Example: How to Use TD_RegressionEvaluator
TD_ROC
TD_ROC Syntax
Required Syntax Elements for TD_ROC
Optional Syntax Elements for TD_ROC
TD_ROC Input
TD_ROC Output
Example: How to Use TD_ROC
TD_SHAP
TD_SHAP Syntax
Required Syntax Elements for TD_SHAP
Optional Syntax Elements for TD_SHAP
TD_SHAP Input
TD_SHAP Output
Example: How to Use TD_SHAP
Regression Model Using TrainingFunction with TD_GLM
Classification Model Using TrainingFunction with TD_XGBoost
TD_Silhouette
TD_Silhouette Syntax
Required Syntax Elements for TD_Silhouette
Optional Syntax Elements for TD_Silhouette
TD_Silhouette Input
TD_Silhouette Output
Example: How to Use TD_Silhouette
TD_TrainTestSplit
TD_TrainTestSplit Syntax
Required Syntax Elements for TD_TrainTestSplit
Optional Syntax Elements for TD_TrainTestSplit
TD_TrainTestSplit Input
TD_TrainTestSplit Output
TD_TrainTestSplit Examples
Text Analytic Functions
TD_NaiveBayesTextClassifierPredict
TD_NaiveBayesTextClassifierPredict Syntax
TD_NaiveBayesTextClassifierPredict Syntax Elements
TD_NaiveBayesTextClassifierPredict Input
TD_NaiveBayesTextClassifierPredict Output
TD_NaiveBayesTextClassifierPredict Examples
TD_NaiveBayesTextClassifierPredict Example: TopK Specified
TD_NaiveBayesTextClassifierPredict Example: Responses Specified
TD_NaiveBayesTextClassifierTrainer
TD_NaiveBayesTextClassifierTrainer Syntax
TD_NaiveBayesTextClassifierTrainer Syntax Elements
TD_NaiveBayesTextClassifierTrainer Input
TD_NaiveBayesTextClassifierTrainer Output
Example: Using TD_NaiveBayesTextClassifierTrainer with Multinomial Model Type
TD_NERExtractor
TD_NERExtractor Syntax
Required Syntax Elements for TD_NERExtractor
Optional Syntax Elements for TD_NERExtractor
TD_NERExtractor Input
TD_NERExtractor Output
Example: How to Use TD_NERExtractor
TD_Ngramsplitter
TD_Ngramsplitter Syntax
Required Syntax Elements for TD_Ngramsplitter
Optional Syntax Elements for TD_Ngramsplitter
TD_Ngramsplitter Input
TD_Ngramsplitter Output
TD_Ngramsplitter Usage Notes
Examples: How to Use TD_Ngramsplitter
TD_Ngramsplitter Examples Input
Example: Omit Accumulate
Example: Specify Accumulate
TD_SentimentExtractor
TD_SentimentExtractor Syntax
TD_SentimentExtractor Syntax ElementsRequired Syntax Elements for TD_SentimentExtractor
TD_SentimentExtractor Input
TD_SentimentExtractor Output
TD_SentimentExtractor Examples
TD_TextParser
TD_TextParser Syntax
Required Syntax Elements for TD_TextParser
Optional Syntax Elements for TD_TextParser
TD_TextParser Input
TD_TextParser Output
TD_TextParser Example
TD_TFIDF
TD_TFIDF Syntax
Required Syntax Elements for TD_TFIDF
Optional Syntax Elements for TD_TFIDF
TD_TFIDF Input
TD_TFIDF Output
Example: How to Use TD_TFIDF
TD_WordEmbeddings
TD_WordEmbeddings Syntax
Required Syntax Elements for TD_WordEmbeddings
Optional Syntax Elements for TD_WordEmbeddings
TD_WordEmbeddings Input
TD_WordEmbeddings Output
Example: How to Use TD_WordEmbeddings
Hypothesis Testing Functions
Hypothesis Test Components
Hypothesis Test Types
TD_ANOVA
TD_ANOVA Syntax
Required Syntax Elements for TD_ANOVA
Optional Syntax Elements for TD_ANOVA
TD_ANOVA Input
TD_ANOVA Output
Examples: How to Use TD_ANOVA
Using TD_ANOVA to Determine Difference of Insect Sprays
Using GroupNames Argument
Using NumGroups Argument
TD_ChiSq
TD_ChiSq Syntax
Required Syntax Elements for TD_ChiSq
Optional Syntax Elements for TD_ChiSq
TD_ChiSq Input
TD_ChiSq Output
TD_ChiSq Usage Notes
TD_FTest
TD_FTest Syntax
Required Syntax Elements for TD_FTest
Optional Syntax Elements for TD_FTest
TD_FTest Input
TD_FTest Output
TD_FTest Usage Notes
Examples: How to Use TD_FTest
Using FirstSampleVariance and SecondSampleVariance Arguments
Using FirstSampleName and SecondSampleName Arguments
Using FirstSampleName and SecondSampleVariance Arguments
Using SecondSampleName and FirstSampleVariance Arguments
TD_ZTest
TD_ZTest Syntax
Required Syntax Elements for TD_ZTest
Optional Syntax Elements for TD_ZTest
TD_ZTest Input
TD_ZTest Output
TD_ZTest Usage Notes
Examples: How to Use TD_ZTest
Using Two-tailed Test
Example: Using Two Samples
Example: Using One Sample
Association Analysis Functions
TD_Apriori
TD_Apriori Syntax
Required Syntax Elements for TD_Apriori
Optional Syntax Elements for TD_Apriori
TD_Apriori Input
TD_Apriori Output
Examples: How to use TD_Apriori
Example 1: Sparse Input
Example 2: Dense Input
TD_CFilter
TD_CFilter Syntax
Required Syntax Elements for TD_CFilter
Optional Syntax Elements for TD_CFilter
TD_CFilter Input
TD_CFilter Output
TD_CFilter Usage Notes
Example: How to Use TD_CFilter
Path and Pattern Analysis Functions
Terminology
Attribution
Attribution Syntax
Attribution Syntax Elements
Attribution Input
Model Specification
Attribution Output
Example: Model Assigns Attribution Weights to Events and Channels
nPath
nPath Syntax
nPath Syntax Elements
nPath Input
nPath Output
nPath Symbols
LAG and LEAD Expressions in Symbol Predicates
LAG Expression Syntax
LAG and LEAD Expression Rules
LAG and LEAD Expressions Example: Alias for Input Query
LAG and LEAD Expressions Example: No Alias for Input Query
nPath Patterns
nPath Greedy Pattern Matching
nPath Filters
nPath Filters Example
nPath Results
nPath Results Examples
nPath Results Example: FIRST, LAST_NOTNULL, MAX_CHOOSE, and MIN_CHOOSE
nPath Results Example: FIRST and Three Forms of ACCUMULATE
nPath Results Example: FIRST, Three Forms of ACCUMULATE, COUNT, and NTH
nPath Results Example: Combine Values from One Row with Values from the Next Row
nPath Results Example: ACCUMULATE String over 64000 Characters
nPath Results Example: ACCUMULATE String over 64000 Characters, DISTINCT
nPath Results Example: ACCUMULATE String over 64000 Characters, CDISTINCT
nPath Results Example: Hindi Input, ACCUMULATE FIRST_NOTNULL
nPath Results Example: Hindi Input, ACCUMULATE DISTINCT and CDISTINCT
nPath Examples
Symbols and Symbol Predicates That Examples Use
nPath ClickStream Data Examples
nPath Range-Matching Examples
nPath Range-Matching Example: Accumulate Pages Visited in Each Session
nPath Range-Matching Example: Find Sessions That Start at Home Page and Visit Page1
nPath Range-Matching Example: Find Paths to Checkout Page for Purchases Over $200
nPath Range-Matching Example: Use OVERLAPPING Mode
nPath Range-Matching Example: Find First Product with Multiple Referrers in Any Session
nPath Range-Matching Example: Find Data for Sessions That Checked Out 3-6 Products
nPath Range-Matching Example: Find Data for Sessions That Checked Out at Least 3 Products
nPath Range-Matching Example: Multiple Partitioned Input Tables and Dimension Input Table
Sessionize
Sessionize Syntax
Required Syntax Elements for Sessionize
Optional Syntax Elements for Sessionize
Sessionize Input
Sessionize Output
Example: How to Use Sessionize
Text Analytics AI Functions
Key Features and Additions
Common Functionality or Rules
Azure CSP LLM Syntax
AWS Bedrock CSP LLM Syntax
Google Gemini LLM Syntax
NVIDIA NIM Hosted Models Syntax
Lite LLM Hosted Models Syntax
Text Analytics AI Function Example Input
AI_AnalyzeSentiment
AI_AnalyzeSentiment Syntax
Cloud Service Provider Authentication for AI_AnalyzeSentiment
Syntax Elements for AI_AnalyzeSentiment
AI_AnalyzeSentiment Input
AI_AnalyzeSentiment Output
Examples: How to Use AI_AnalyzeSentiment
AI_AskLLM
AI_AskLLM Syntax
Cloud Service Provider Authentication for AI_AskLLM
Syntax Elements for AI_AskLLM
AI_AskLLM Input
AI_AskLLM Output
Examples: How to Use AI_AskLLM
AI_DetectLanguage
AI_DetectLanguage Syntax
Cloud Service Provider Authentication for AI_DetectLanguage
Syntax Elements for AI_DetectLanguage
AI_DetectLanguage Input
AI_DetectLanguage Output
Examples: How to Use AI_DetectLanguage
AI_ExtractKeyPhrases
AI_ExtractKeyPhrases Syntax
Cloud Service Provider Authentication for AI_ExtractKeyPhrases
Syntax Elements for AI_ExtractKeyPhrases
AI_ExtractKeyPhrases Input
AI_ExtractKeyPhrases Output
Examples: How to Use AI_ExtractKeyPhrases
AI_MaskPII
AI_MaskPII Syntax
Cloud Service Provider Authentication for AI_MaskPII
Syntax Elements for AI_MaskPII
AI_MaskPII Input
AI_MaskPII Output
Examples: How to Use AI_MaskPII
AI_RecognizeEntities
AI_RecognizeEntities Syntax
Cloud Service Provider Authentication for AI_RecognizeEntities
Syntax Elements for AI_RecognizeEntities
AI_RecognizeEntities Input
AI_RecognizeEntities Output
Examples: How to Use AI_RecognizeEntities
AI_RecognizePIIEntities
AI_RecognizePIIEntities Syntax
Cloud Service Provider Authentication for AI_RecognizePIIEntities
Syntax Elements for AI_RecognizePIIEntities
AI_RecognizePIIEntities Input
AI_RecognizePIIEntities Output
Examples: How to Use AI_RecognizePIIEntities
AI_TextClassifier
AI_TextClassifier Syntax
Cloud Service Provider Authentication for AI_TextClassifier
Syntax Elements for AI_TextClassifier
AI_TextClassifier Input
AI_TextClassifier Output
Examples: How to Use AI_TextClassifier
AI_TextEmbeddings
AI_TextEmbeddings Syntax
Cloud Service Provider Authentication for AI_TextEmbeddings
Syntax Elements for AI_TextEmbeddings
AI_TextEmbeddings Input
AI_TextEmbeddings Output
Examples: How to Use AI_TextEmbeddings
AI_TextSummarize
AI_TextSummarize Syntax
Cloud Service Provider Authentication for AI_TextSummarize
Syntax Elements for AI_TextSummarize
AI_TextSummarize Input
AI_TextSummarize Output
Examples: How to Use AI_TextSummarize
AI_TextTranslate
AI_TextTranslate Syntax
Cloud Service Provider Authentication for AI_TextTranslate
Syntax Elements for AI_TextTranslate
AI_TextTranslate Input
AI_TextTranslate Output
Examples: How to Use AI_TextTranslate
Build Scalable Analytics with Open Analytics Framework
Introduction to Vantage Open Analytics
A Historical Perspective of Python and R in Teradata
What is Open Analytics Framework
Why Use Open Analytics Framework
When to Use Open Analytics Framework
How Open Analytics Framework Works
Requisite Tools and Libraries
Requisite Input and Output Structures
Data Science Workflows using Open Analytics Framework
Setting Up VantageCloud Lake for Open Analytics
Creation and Management of Analytic and Analytic GPU Compute Groups
User Profile
User Sessions
User Environments
Overview of APIs for User Environment Operations
Conda Integration
Open Analytics Python conda User Environment
Bring Your Own LLM and DL Workloads
How It Works
Before You Begin
Admin: Set Up VantageCloud Lake for Bring Your Own LLM/DL Using the Console
Using the Open Analytics Framework for LLM/DL
Using Hugging Face LLMs
Using User Environment APIs to Manage LLMs
Usage Notes and Limitations
Sample LLM Use Cases
APPLY Table Operator
Sample Use Cases in Open Analytics Framework
Prerequisites for All Use Cases
Use Cases using Python Environments
Bank Marketing Model Training and Prediction
Set Up and Manage a User Environment
Load the Dataset and Prepare for Training
Run the Python Training Script
Run the Bank Marketing Training
Score the Prediction Model
Clean Up after Bank Marketing Use Case
Scoring with an Externally Trained Model File
Set Up and Manage the User Environment
Install the Model and Python Script Files
Score the Predictive Model with APPLY Table Operator
Clean Up after Scoring with External Model FIle
Training and Scoring Multiple Micro Models for Each Partition
Set Up and Manage the User Environment
Load Data for Training
Start the Model Training
Deploy the Model In the User Environment
Clean Up after Micro Model Use Case
K-Means Clustering Classification
Set Up and Managing the User Environment
Install the Python Script File
Run Clustering Analysis with APPLY Table Operator
Clean up after K-Means Clustering Classification
Simulation
Set Up and Manage the User Environment
Install the Python Script File
Run the Simulation Analysis with APPLY Table Operator
Clean Up after Simulation Analysis
Examples with teradataml.DataFrame.apply Method
Set Up and Manage the User Environment
Example 1: Removing Stopwords from Text
Example 2: Normalizing Data
Clean Up after teradatam.DataFrame.apply
Use Cases using Python Conda Environments
Predicting Next Value Using Keras
Set Up and Manage the User Environment
Install the Python Script Files
Run the Keras Script with APPLY Table Operator
Clean Up after Python Conda Use Cases
Sentiment Analysis
Set Up and Manage the User Environment
Install the Python Script Files
Run Sentiment Analysis with APPLY Table Operator
Clean Up after Sentiment Analysis
Use Cases using R Environments
Gradient Boosting
Set Up and Manage the User Environment
Install the R Script Files
Run the Gradient Boosting Algorithm with APPLY Table Operator
Clean Up after Gradient Boosting
Natural Language Processing
Set Up and Manage the User Environment
Install the R Script Files
Tokenize the Text with APPLY Table Operator
Clean Up after Natural Language Processing
Combining Multidimensional Arrays
Set Up and Manage the User Environment
Install the R Script Files
Combine Multidimensional Arrays with APPLY Table Operator
Clean Up after Combining Multidimensional Arrays
Additional Information and Best Practice Tips
Converting Scripts to Use with Open Analytics Framework
Best Practice Tips
Optimal Use Cases
Use Cases Dos and Don'ts
System Resources - Memory
Preventing Unwanted Output
Production Deployment
Troubleshooting
Teradata Package for Python on VantageCloud Lake
Introduction to Teradata Package for Python
Teradata Package for Python Product Overview
The teradataml Package
Key Feature Additions and Changes
Teradata Package for Python Function Reference on VantageCloud Lake
Installing, Uninstalling, and Upgrading Teradata Package for Python
Installing Teradata Package for Python
Teradata Package for Python System Requirements
Installing Open Source Python on the Client
Installing Teradata Package for Python on a Client Through PyPI
Install Teradata Package for Python on Windows
Install the Teradata Package for Python on macOS or Linux OS
Install Teradata Package for Python on IBM PowerPC
Common Issues and Solutions with Installing Teradata Package for Python on IMB PowerPC
Complete Environment Setup Script
Usage Recommendations (Teradata Package for Python on IBM PowerPC)
Installing Teradata Package for Python from Teradata Downloads
Download Teradata Package for Python from Teradata Downloads
Install Teradata Python Package on Windows from the Wheel File
Install Teradata Python Package on macOS or Linux OS from the Wheel File
Test teradataml Connection to Vantage
Uninstall the Teradata Package for Python
Upgrade the Teradata Package for Python
Uninstall the Teradata Package for Python
Upgrade the Teradata Package for Python
teradataml Components
Helper Functions
load_example_data() Function
Garbage Collection in teradataml
Run SQL Queries using teradataml
DataFrames for Tables and Views
DataFrames from Teradata Vantage Data Sources
DataFrame Constructor
DataFrame.from_table() Function
DataFrame.from_query() Function
DataFrame.from_pandas Function
DataFrame.from_dict Function
DataFrame.from_records Function
Access Tables in a Non-Default Database in Vantage
Access OTF Tables
Accessing OTF data from time travel information
get_snapshot
Input Classes for UAF Functions
TDSeries
TDAnalyticResult
TDMatrix
TDGenSeries
DataFrame Manipulation
select() Method
drop() Method
dropna() Method
assign() Method
Regular Aggregate Functions Supported by DataFrame
groupby() Method
Time Series Aggregates
Example Setup
groupby_time()
resample()
Time Series Aggregate Functions
concat() Method
describe() Method
Regular Aggregate Mode Examples for describe()
Time Series Aggregate Mode Examples for describe()
alias() Method
Filtering Rows and Columns
filter() Method
item based Filtering
substring based Filtering
regex Filtering
index[] Operator
fillna() Method
get() Method
get_values() Method
head and tail
head() Method
tail() Method
itertuples() Method
join() Method
iloc[] Operator
loc[] Operator
merge() Method
sample() Method
set_index() Method
show_query() Method
sort() Method
sort_index() Method
squeeze() Method
drop_duplicate() Function
cube() Function
rollup() Function
replace()
DataFrame Metadata
info() Method
keys() Method
DataFrame Properties
columns Property
dtypes Property
index Property
shape Property
size Property
tdtypes Property
db_object_name Property
Data Rotation
pivot()
unpivot()
Access metadata for OTF tables
history
manifests
history
snapshots
Saving teradataml DataFrames to Vantage
to_sql() DataFrame Method
Exporting DataFrame to External Entities
to_pandas() Method
to_csv() Method
Executing Python Functions Inside Database Engine 20
Use of teradataml UDF versus DataFrame Methods
teradataml UDF
teradataml UDF Prerequisites
udf - Function decorator
Using udf Decorator without Arguments
Using udf Decorator with Arguments
Examples: How to Use udf()
udf() Example Setup
udf() Examples
register()
list_udfs()
call_udf()
deregister()
UDF Functions Examples
Example Setup
Examples: How to Use teradataml UDF Functions
DataFrame Methods
DataFrame.apply()
DataFrame.apply() Setup and Usage
DataFrame.apply() Arguments
Examples: How to use DataFrame.apply()
teradataml DataFrame Column
Access teradataml DataFrame Column
teradataml DataFrame Column Manipulation
alias()
isin()
NA Checking: isna()/notna() and isnull()/notnull() Methods
Type Casting: cast()
SQL Functions
to_numeric
case
desc
asc
distinct
String Manipulation
contains() Method
lower() Method
strip() Method
Regular Aggregate Functions Supported by DataFrame Column
Date Time Functions
String Functions
Regular Arithmetic Functions
Bit Byte Manipulation Functions
Regular Expression Functions
Comparison Functions
Trigonometric Functions
Hyperbolic Functions
teradataml Window Aggregates
Window on DataFrame
Window on DataFrame Column
Window Aggregate Functions
Context to Teradata Vantage
create_context
Create connection using config file
Create a connection using environment variables
Order of preference between config file, environment variables and arguments of create_context
get_context
get_connection
set_context
remove_context
teradataml General Functions
Data Transfer Utility
Saving DataFrame to Vantage
copy_to_sql()
fastload()
fastexport()
Loading Data from CSV to Vantage
read_csv
Data Transfer between Vantage and Cloud Storage
Prerequisites
Create Authorization Object
Create Function Mapping
ReadNOS
WriteNOS
Database Utility
db_drop_table()
db_drop_view()
db_list_tables()
db_python_package_details()
db_python_package_version_diff
db_python_version_diff
display_analytic_functions()
list_td_reserved_keywords()
view_log()
File Management Functions
install_file()
remove_file()
list_files()
Miscellaneous Functions
print_options()
show_versions()
execute_sql()
async_run_status()
td_range()
get_formatters()
Apply SET Operations on teradataml DataFrames
concat
td_except
td_intersect
td_minus
teradataml Options
Configuration Options
default_varchar_size
temp_table_database and temp_view_database
byom_install_location
val_install_location
database_version
read_nos_function_mapping
write_nos_function_mapping
inline_plot
certificate_file
table_operator
openml_user_env
local_storage
stored_procedure_install_location
temp_object_type
use_short_object_name
Display Options
byte_encoding
max_rows
precision
print_sqlmr_query
blob_length
suppress_vantage_runtime_warnings
geometry_column_length
enable_ui
set_config_params
Series
Series from teradataml DataFrame
Series Manipulation
head()
unique()
Series Metadata
name
BYOM
Supported External Model Types
PMMLPredict
H2OPredict
ONNXPredict
DataikuPredict
DataRobotPredict
save_byom()
list_byom()
retrieve_byom()
delete_byom()
set_byom_catalog()
set_license()
get_license()
BYOM Workflows
Working with Geospatial Data
teradataml Geometry Types
Point
LineString
Polygon
MultiPoint
MultiLineString
MultiPolygon
GeometryCollection
GeoSequence
teradataml GeoDataFrame
Access Geospatial Data on Vantage
GeoDataFrame Properties
GeoDataFrame Methods
teradataml GeoDataFrameColumn
Access Individual Geometry Columns
GeoDataFrameColumn Properties and Methods Specific to Geospatial Data
Use Case 1: Run a Single Geospatial Function
Use Case 2: Run Multiple Geospatial Functions
Use Case 3: Filtering using Geospatial Functions
GeoDataFrameColumn Properties
GeoDataFrameColumn Methods
Exploratory Data Analysis
Enable or Disable EDA UI
EDA UI Tabs
Plotting in teradataml
Types of Plots
Bar Plot
Correlation Plot
Geometry Plot
Line Plot
Mesh Plot
Scatter Plot
Wiggle Plot
Combine Multiple Plots into a Single Plot
Composite Plot
Compositing Line Plot
Compositing Correlation Plot
Subplot
Subplotting with Every Individual Plot Occupies Same Area in Figure
Subplotting with Every Individual Plot Occupies Different Areas in Figure
Options for Plotting
Axis
Figure
Options Available for Plot Method
Hyperparameter Tuning in teradataml
GridSearch
Methods of GridSearch
_init_
fit
evaluate
predict
get_error_log
get_input_data
get_model
get_parameter_grid
is_running
set_model
Properties of GridSearch
best_data_id
best_model
best_model_id
best_params_
best_sampled_data_
best_score_
model_stats
models
Examples for GridSearch
Example 1: Using Hyperparameter Tuning for Model Trainer Function
Example 2: Input Data Hyper-parameterization for Model Trainer Function Tuning
Example 3: Hyperparameter Tuning Operations on Non-Model Trainer Function
Example 4: Parallelization in Hyperparameter Tuning for Model and Non-Model Trainer Functions
Example 5: Early Stopping Methods in Hyperparameter Tunning
Example 5 Setup
Example 5.1: Time Based Early Stopping for Model Trainer Function
Example 5.2: Time Based Early Stopping for Non-Model Trainer Function
Example 5.3: Metrics Based Early Stopping for Model Trainer Function
RandomSearch
Methods of RandomSearch
_init_
fit
evaluate
predict
get_error_log
get_input_data
get_model
get_parameter_grid
is_running
set_model
Properties of RandomSearch
best_data_id
best_model
best_model_id
best_params_
best_sampled_data_
best_score_
model_stats
models
Examples for RandomSearch
Example 1: Using Hyperparameter Tuning for Model Trainer Function
Example 2: Input Data Hyper-parameterization for Model Trainer Function Tuning
Example 3: Hyperparameter Tuning Operations on Non-Model Trainer Function
Example 4: Parallelization in Hyperparameter Tuning for Model and Non-Model Trainer Functions
Example 5: Early stopping methods in hyperparameter tunning
Example 5 Setup
Example 5.1: Time Based Early Stopping for Model Trainer Function
Example 5.2: Time Based Early Stopping for Non-Model Trainer Function
Example 5.3: Metrics Based Early Stopping for Model Trainer Function
AutoML in teradataml
Key Features of AutoML
Methods of AutoML
AutoML.__init__
AutoRegressor.__init__
AutoClassifier.__init__
fit
leaderboard
leader
predict
generate_custom_config
get_persisted_tables
visualize
AutoML Examples
Example 1: Run AutoML for Regression Problem with Early Stopping Timer and Metrics Threshold
Example 2: Run AutoRegressor for Regression Problem with Early Stopping Condition and Customization
Example 3: Run AutoClassifier for Classification Problem using Early Stopping Timer
Example 4: Run AutoML for classification problem using early stopping timer, max_models and customization
Example 5: Run AutoML for multiclass classification problem using early stopping timer and max_models
Example 6: Run AutoClassifier for Multiclass Classification Problem using Early Stopping Timer
Example 7: Run Trained AutoML Models across Multiple Sessions using deploy and load APIs
AutoDataPrep
Key Features of AutoDataPrep
Methods of AutoDataPrep
AutoDataPrep.__init__
fit
get_data
load
deploy
delete_data
visualize
AutoDataPrep Examples
Example 1: AutoDataPrep for Regression problem
Example 2: AutoDataPrep for Classification Problem
Feature Store in teradataml
Feature Store Components
Feature Object
Entity Object
DataSource Object
FeatureGroup Object
Combining one or more Feature Groups into a single FeatureGroup
FeatureStore Object
Setting up FeatureStore
FeatureStore Methods
Add a component to FeatureStore
Get the FeatureStore Components
Modify an existing component in FeatureStore
Search for components in FeatureStore
Get dataset from FeatureStore
Remove components from FeatureStore
Disable and enable Features without Removing them from FeatureStore
Manage Access for FeatureStore
Use FeatureStore in teradataml Analytic Functions
teradataml Open-Source Machine Learning Functions
teradataml OpenSourceML Setup and Requirements
When Client is Connected to VantageCloud Enterprise
When Client is Connected to VantageCloud Lake
td_sklearn
Run scikit-learn Functions using Legacy Arguments
Run scikit-learn Functions using Teradata Introduced Arguments
Support for Distributed Modeling
Support for Classification and Regression Metrics
Support for Model Operations using td_sklearn
Example: Deploy and Load Distributed Model
Example: Deploy and Load Single Model
Example: Deploy and Load Model Trained outside Vantage
td_sklearn Supportability Matrix
Support for Model Operations
Model Deployment
Model Loader
td_sklearn
Run scikit-learn Functions using Legacy Arguments
Run scikit-learn Functions using Teradata Introduced Arguments
Support for Distributed Modeling
Support for Classification and Regression Metrics
Support for Model Operations using td_sklearn
Example: Deploy and Load Distributed Model
Example: Deploy and Load Single Model
Example: Deploy and Load Model Trained outside Vantage
td_sklearn Supportability Matrix
td_lightgbm
Execute lightGBM functions using standard supported arguments
Single model training
Single model cross validation
Multi model training
Multi model cross validation
Using Booster for prediction
Single model prediction
Multi model prediction
Running scikit-learn API
Single model case - LGBMRegressor
Multi model case - LGBMClassifier
Support for Model Operations using td_lightgbm
Data preparation
Example: Single model deployment and loading of td_lightgbm Booster trained in Vantage
Example: Distributed model deployment and loading of td_lightgbm Booster trained in Vantage
Example: Single model deployment and loading of td_lightgbm sklearn model trained in Vantage
Example: Distributed model deployment and loading of td_lightgbm sklearn model trained in Vantage
Example: Deploy and load the Booster model trained outside Vantage using train()
Example: Deploy and load the sklearn model trained outside Vantage
td_lightgbm Supportability Matrix
td_lightgbm Usage Notes
Limitations and Considerations
Working with Open Analytics
Complete Prerequisites to Use Open Analytics Framework
Class to Use with Open Analytics Framework
set_auth_token
APIs to Use with Open Analytics Framework
APIs to Manage User Environments
list_base_envs
create_env
list_user_envs
remove_env
remove_all_envs
APIs to Get Handler for Remote User Environment
get_env
APIs to Manage Files, Libraries, and Models inside a User Environment
files
install_file
remove_file
libs
install_lib
update_lib
uninstall_lib
models
install_model
uninstall_model
status
refresh
snapshot
teradataml Apply Class for APPLY Table Operator
Apply Function
Example 1: Working with Python Script
Example 2: Working with R Script
execute_script
set_data
deploy
Open Analytics Workflows
Using Teradata Vantage Analytic Functions with Teradata Package for Python
Usage Notes
Column Specification in Engine 20 In-Database Analytic Functions
load_example_data() Function
Use Cases
Text Analysis with teradataml Package
Use ClassificationEvaluator to Evaluate the Classification
Use GLM Model with teradataml Package
Use Decision Forest Model with teradataml Package
Use the KMeans Clustering Function with teradataml Package
Churn Analysis Using Sessionize and NPath with Teradata Package for Python
Use DataFrame.map_partition() Function for GLM Model Fitting and Scoring Functions
Use PMMLPredict to Score using Externally Trained Models
Use H2OPredict to Score using Externally Trained Models
Use ONNXPredict to Score using Externally Trained Models
Use Open Analytics to Score using Externally Trained Models using Apply
Python SDK support in teradataml
ModelOps SDK
blueprint() function
ModelOpsClient class
REST APIs classes and methods
Schema related classes
Teradata Package for Python Limitations and Considerations
Teradata Package for Python Limitations
Open Analytics Login Issue with teradataml 17.20.00.05 and 17.20.00.06
DataFrame Creation on Primary Time Index Tables is Partially Supported
copy_to_sql and to_sql Functions Limitation
Multithreading and Concurrent Usage Limitations
print(dataframe.dtypes) Displays Column Types as String
Error Calling teradataml Analytic Functions
select() Method Requires Unique Column Names
Limited Missing Value Support
DataFrames Become Invalid When a Connection Context is Recreated
Error Using responses Argument in MLE Function NaïveBayesTextClassifierPredict
copy_to API When Loading Data into PTI Table
Exploratory Data Analysis UI (EDA UI)
Working with OTF Tables
Teradata Package for Python Considerations
SQLAlchemy Compatibility Considerations
User Permissions in Vantage
Persistence of Tables Created by the teradataml Package in Vantage
Filtering with Boolean Column Requires a Comparison
String Comparisons may be Case Insensitive
Working with OTF Tables
Teradata Python Package Import
charset argument in Vantage Analytics Library Functions
Install PyYAML Python package for using SDK
Teradata Package for Python Issues with VIEW Creation
SQL versus teradataml Differences
Issue while Creating a teradataml DataFrame from a Table in Non-Default Database
Issue of not Having PERM SPACE to Create Temporary Tables
Issue while Accessing a View in other Schema
CREATE VIEW and SELECT WITH [non_default_database].[any_view] Issue Solution
Using teradataml with Native Object Store
Data in JSON or CSV Format
Example: Create teradataml DataFrame on NOS foreign table in JSON data format
Example: Create teradataml DataFrame on NOS foreign table in CSV data format
Accessing Columns and Path Variables using DataFrame.from_query()
Accessing Columns and Path Variables by Creating a View on Foreign Table
Accessing Columns and Path Variables by Creating a Table from Foreign Table
Data in Parquet Format
Accessing Foreign Table Created On Parquet Data
Accessing Path Variables using DataFrame.from_query()
Accessing Path Variables by Creating a View on Foreign Table in Vantage
Accessing Path Variables by Creating a Table from Foreign Table
teradataml Extension with SQLAlchemy
Accessing Vantage SQL Functions
Example: Accessing Vantage SQL Function with SQLAlchemy
Supported SQL Functions
Aggregate Functions
Arithmetic, Hyperbolic and Trigonometric Functions
Bit Byte Manipulation Functions
Built-In Functions
Hash Related Functions
Regular Expression Functions
String Functions
Window Aggregate Functions
Using SQLAlchemy Clause Element and Expression
Using Basic SQLAlchemy ClauseElement and Expression in DataFrame.assign()
Using Basic SQLAlchemy ClauseElement and Expression for Filtering
Data Type Mapping between Database Engine 20, teradataml DataFrame dtypes, and Python
Teradata pyspark2teradataml
Introduction to Teradata pyspark2teradataml
Key Feature Additions and Changes
Installing teradatamlspk Package
teradatamlspk Package System Requirements
Install teradatamlspk on a Windows OS,macOS, Linux Client
PySpark to Vantage Migration
Step1: Run pyspark2teradataml with PySpark Script/Notebook as Input
Step 2: Review the HTML Report
Limitations and Considerations
Examples with pyspark2teradataml
Example: Create teradatamlspk DataFrame for Data in a Vantage Table or View
Examples: Partially Supported Functions
shiftright
shiftleft
cast
agg
crosstab
replace
join
crossJoin
orderBy and Sort
createTempView
createOrReplaceTempView
colRegex
unpivot
melt
pivot
fillna and na.fill
Read Parquet File
Read JSON File
Read CSV File
Write Parquet File
Write CSV File
Write orc File
Write json File
Write saveAsTable
Write insertInto
writeTo create
writeTo createOrReplace
writeTo replace
writeTo append
writeTo partitionedBy
MaxAbsScaler
OneHotEncoder
UnivariateFeatureSelector
VarianceThresholdSelector
RegexTokenizer
Example: Use Pipeline Functionality
Use Pipeline in PySpark
Use Pipeline through teradataml Open-Source Machine Learning Functions
Example: Work with StandardScaler Function
Work with PySpark StandardScaler Function
Work with teradatamlspk StandardScaler Function
PySpark API Supportability Matrix
Spark SQL
SparkSession APIs
Input
DataFrame APIs
Column APIs
Data Types
Functions
Window
Grouping
UDF
MLLib (DataFrame-Based) Classes
Binarizer
BinaryLogisticRegressionSummary
BinaryLogisticRegressionTrainingSummary
BinaryRandomForestClassificationSummary
BinaryRandomForestClassificationTrainingSummary
Bucketizer
ChiSquareTest
ClusteringEvaluator
DecisionTreeClassificationModel
DecisionTreeClassifier
DecisionTreeRegressionModel
DecisionTreeRegressor
GaussianMixture
GaussianMixtureModel
GaussianMixtureSummary
GBTClassificationModel
GBTClassifier
GBTRegressionModel
GBTRegressor
Imputer
ImputerModel
KMeans
KMeansModel
KMeansSummary
ImputerModel
IsotonicRegression
IsotonicRegressionModel
LinearRegression
LinearRegressionModel
LinearRegressionSummary
LinearRegressionTrainingSummary
LinearSVC
LinearSVCModel
LinearSVCSummary
LinearSVCTrainingSummary
LogisticRegression
LogisticRegressionModel
LogisticRegressionSummary
LogisticRegressionTrainingSummary
MaxAbsScaler
MaxAbsScalerModel
MinMaxScaler
MinMaxScalerModel
MulticlassClassificationEvaluator
MultilayerPerceptronClassifier
MultilayerPerceptronClassificationModel
MultilayerPerceptronClassificationSummary
MultilayerPerceptronClassificationTrainingSummary
NaiveBayes
NaiveBayesModel
OneHotEncoder
OneHotEncoderModel
OneVsRest
OneVsRestModel
PCA
PCAModel
RandomForestClassificationModel
RandomForestClassificationSummary
RandomForestClassificationTrainingSummary
RandomForestClassifier
RandomForestRegressionModel
RandomForestRegressor
RegexTokenizer
RegressionEvaluator
RobustScaler
RobustScalerModel
SQLTransformer
StandardScaler
StandardScalerModel
VarianceThresholdSelector
VarianceThresholdSelectorModel
UnivariateFeatureSelector
UnivariateFeatureSelectorModel
VectorAssembler
Teradataml Widgets on VantageCloud Lake
Introduction to Teradataml Widgets
Compatibility Development Environment
Key Feature Additions and Changes
Installing and Setting up teradatamlwidgets
Install teradatamlwidgets
teradatamlwidgets Package System Requirements
Set up teradatamlwidgets for login
login.Ui
Using Teradataml Widgets with Analytic Functions
Run teradatamlwidgets using Analytic Functions
Teradataml Widgets Toolbar Button Functionality
analytic_functions.Ui
get_output_dataframe
Analytic Function Examples
Database Engine 20 Function Example: Moving Average
VAL Function Example: Linear Regression
VAL Example: Linear Regression Predict
UAF Example: TD_RESAMPLE
Using Teradataml Widgets with AutoML
auto_ml.Ui
AutoML Methods
Set up AutoML teradataml Widgets
Example: How to Use AutoML with Teradataml Widgets
Using Teradataml Widgets with Plot
plot.Ui
Set up the Plot teradataml Widgets
Plot Teradataml Widgets Tabs
Plot Examples
Example 1: Simple Line Plot
Example 2: Simple Bar Plot
Example 3: Composite Bar Plot
Example 4: Scatter Plot
Example 5: Simple Mesh Plot
Example 6: Simple Wiggle Plot
Example 7: Geometry Plot
Creating Subplots Using ShowPlots()
Using Teradataml Widgets with BYOM Scoring
byom_functions.Ui
Set up BYOM Scoring Functions in Teradataml Widgets
Example: How to Use BYOM Scoring Model with Teradataml Widgets
Using Teradataml Widgets with Script Table Operator
script.Ui
Set up Script Table Operator in Teradataml Widgets
Example: How to Use Script Table Operator with Teradataml Widgets
Using Teradataml Widgets with Exploratory Data Analysis (EDA)
eda.Ui
Set up EDA in Teradataml Widgets
EDA Teradataml Widgets Tabs
Using Teradataml Widgets with Describe
describe.Ui
Set up Describe in Teradataml Widgets
Example: Describe in teradataml Widgets
Using Teradataml Widgets with Persist
persist.Ui
Set up Persist in Teradataml Widgets
Example: How to Use Persist with Teradataml Widgets
tdnb
tdnb.text()
tdnb.dropdown()
tdnb.multi_select()
tdnb.get()
tdnb.get_all()
tdnb.remove()
tdnb.remove_all()
tdnb.run_notebook()
tdnb.exit()
Teradataml Widgets Limitations and Considerations
Teradataml Widgets Limitation
Using Teradataml Widgets in Alteryx
Use Teradataml Widgets in Alteryx
Using Plot Parameters
Plot Parameters
Teradata Package for Generative AI
Introduction to Teradata Package for Generative AI
Key Features and Additions
Teradata Package for Generative AI Resources
Teradata Package for Generative AI Function Reference on VantageCloud Lake
Installing, Uninstalling, and Upgrading Teradata Package for Generative AI
Teradata Package for Generative AI System Requirements
Installing Open Source Python on the Client
Installing Teradata Package for Generative AI on a Client Through PyPI
Install teradatagenai package on Windows
Install teradatagenai package on macOS or Linux OS
Installing Teradata Package for Generative AI from Teradata Downloads
Download Teradata Package for Generative AI from Teradata Downloads
Install teradatagenai package on Windows from wheel file
Install teradatagenai package on macOS or Linux OS from wheel file
Uninstalling Teradata Package for Generative AI
Uninstall Teradata Package for Generative AI on Windows
Uninstall Teradata Package for Generative AI on macOS or Linux OS
Upgrading Teradata Package for Generative AI
Upgrade Teradata Package for Generative AI on Windows
Upgrade Teradata Package for Generative AI on macOS or Linux OS
Teradata Package for Generative AI Functionality
Perform Text Analytics using AI and Vantage
Helper Functions
load_data()
load_data() Parameters
Examples: How to use load_data()
TeradataAI Class
Download and Set up the Environment
TeradataAI Parameters
Examples: How to use TeradataAI
TeradataAI Functions
get_llm()
remove()
get_env()
get_model_args
get_llm_params
task
task() Parameters
Examples: How to use task
TextAnalyticsAI Class
TextAnalyticsAI Example Setup
teradatagenai Workflows
analyze_sentiment()
analyze_sentiment Parameters
Examples: How to use analyze_sentiment()
classify()
classify() Parameters
Examples: How to use classify()
detect_language()
detect_language Parameters
Examples: How to use detect_language()
embeddings()
embeddings() Parameters
Examples: How to use embeddings()
extract_key_phrases()
extract_key_phrases Parameters
Examples: How to use extract_key_phrases()
mask_pii()
mask_pii Parameters
Examples: How to use mask_pii
recognize_entities()
recognize_entities() Parameters
Examples: How to use recognize_entities()
recognize_pii_entities()
recognize_pii_entities Parameters
Examples: How to use recognize_pii_entries
summarize()
summarize() Parameters
Examples: How to use summarize()
translate()
translate() Parameters
Examples: How to use translate()
sentence_similarity()
sentence_similarity() Parameters
Examples: How to use sentence_similarity
ask()
ask() Parameters
Examples: How to use ask()
Teradata Package for Generative AI Limitations and Considerations
Teradata Package for Generative AI Limitations
Google Gemini Model: Masking and Recognition Compatibility
Hugging Face Model Size
Teradata Package for Generative AI Considerations
Persistence of Tables Created by the teradatagenai Package in Vantage
Using Enterprise Vector Store from the Lake Console
AWS: Using Vector Store from the Console
Creating a Vector Store in AWS
Editing a Vector Store
Deleting a Vector Store
Database Unbounded Array Framework Time Series Functions
Unbounded Array Framework Specifications
Series Specifications
SERIES_SPEC Syntax
SERIES_SPEC Syntax Elements
SERIES_SPEC Examples
Matrix Specifications
MATRIX_SPEC Syntax
MATRIX_SPEC Syntax Elements
MATRIX_SPEC Examples
ART Specifications
ART_SPEC Syntax
ART_SPEC Syntax Elements
ART_SPEC Examples
Generated Series Specifications
GENSERIES_SPEC Syntax
GENSERIES_SPEC Syntax Elements
GENSERIES_SPEC Example
Database Unbounded Array Framework Time Series Function Categories
General Utility Functions
Data Preparation Functions
Diagnostic Statistical Test Functions
Model Preparation and Parameter Estimation Functions
Series Forecasting Functions
Temporal and Spatial Functions
General Utility Functions
TD_CONVERTTABLEFORUAF
TD_CONVERTTABLEFORUAF Syntax
TD_CONVERTTABLEFORUAF Syntax Elements
TD_CONVERTTABLEFORUAF Input
TD_CONVERTTABLEFORUAF Output
TD_CONVERTTABLEFORUAF Examples
TD_COPYART
TD_COPYART Syntax
TD_COPYART Syntax Elements
TD_COPYART Input
TD_COPYART Output
TD_COPYART Examples
TD_EXTRACT_RESULTS
TD_EXTRACT_RESULTS Syntax
TD_EXTRACT_RESULTS Syntax Elements
TD_EXTRACT_RESULTS Input
TD_EXTRACT_RESULTS Output
TD_EXTRACT_RESULTS Examples
TD_FILTERFACTORY1D
TD_FILTERFACTORY1D Syntax
TD_FILTERFACTORY1D Syntax Elements
TD_FILTERFACTORY1D Input
TD_FILTERFACTORY1D Output
TD_FILTERFACTORY1D Examples
TD_IMAGE2MATRIX
TD_IMAGE2MATRIX Syntax
TD_IMAGE2MATRIX Syntax Elements
TD_IMAGE2MATRIX Input
TD_IMAGE2MATRIX Output
TD_IMAGE2MATRIX Examples
TD_INPUTVALIDATOR
TD_INPUTVALIDATOR Syntax
TD_INPUTVALIDATOR Syntax Elements
TD_INPUTVALIDATOR Input
TD_INPUTVALIDATOR Output
TD_INPUTVALIDATOR Example
TD_ISFINITE
TD_ISFINITE Syntax
TD_ISFINITE Input
TD_ISFINITE Output
TD_ISFINITE Examples
TD_ISINF
TD_ISINF Syntax
TD_ISINF Input
TD_ISINF Output
TD_ISINF Examples
TD_ISNAN
TD_ISNAN Syntax
TD_ISNAN Input
TD_ISNAN Output
TD_ISNAN Examples
TD_MATRIX2IMAGE
TD_MATRIX2IMAGE Syntax
TD_MATRIX2IMAGE Syntax Elements
TD_MATRIX2IMAGE Input
TD_MATRIX2IMAGE Output
TD_MATRIX2IMAGE Examples
TD_MINFO
TD_MINFO Syntax
TD_MINFO Syntax Elements
TD_MINFO Input
TD_MINFO Output
TD_MINFO Example
TD_PLOT
TD_PLOT Syntax
TD_PLOT Syntax Elements
TD_PLOT Input
TD_PLOT Output
TD_PLOT Usage Notes
TD_PLOT Examples
TD_SINFO
TD_SINFO Syntax
TD_SINFO Syntax Elements
TD_SINFO Input
TD_SINFO Output
TD_SINFO Example
TD_TRACKINGOP
TD_TRACKINGOP Syntax
TD_TRACKINGOP Syntax Elements
TD_TRACKINGOP Input
TD_TRACKINGOP Output
TD_TRACKINGOP Examples
Data Preparation Functions
TD_BINARYSERIESOP
TD_BINARYSERIESOP Syntax
TD_BINARYSERIESOP Syntax Elements
TD_BINARYSERIESOP Input
TD_BINARYSERIESOP Output
TD_BINARYSERIESOP Examples
TD_BINARYMATRIXOP
TD_BINARYMATRIXOP Syntax
TD_BINARYMATRIXOP Syntax Elements
TD_BINARYMATRIXOP Input
TD_BINARYMATRIXOP Output
TD_BINARYMATRIXOP Examples
TD_GENSERIES4FORMULA
TD_GENSERIES4FORMULA Syntax
TD_GENSERIES4FORMULA Syntax Elements
TD_GENSERIES4FORMULA Input
TD_GENSERIES4FORMULA Output
TD_GENSERIES4FORMULA Examples
TD_MATRIXMULTIPLY
TD_MATRIXMULTIPLY Syntax
TD_MATRIXMULTIPLY Syntax Elements
TD_MATRIXMULTIPLY Input
TD_MATRIXMULTIPLY Output
TD_MATRIXMULTIPLY Examples
TD_RESAMPLE
TD_RESAMPLE Syntax
TD_RESAMPLE Syntax Elements
TD_RESAMPLE Input
TD_RESAMPLE Output
TD_RESAMPLE Examples
Diagnostic Statistical Test Functions
TD_BREUSCH_GODFREY
TD_BREUSCH_GODFREY Syntax
TD_BREUSCH_GODFREY Syntax Elements
TD_BREUSCH_GODFREY Input
TD_BREUSCH_GODFREY Output
TD_BREUSCH_GODFREY Example
TD_BREUSCH_PAGAN_GODFREY
TD_BREUSCH_PAGAN_GODFREY Syntax
TD_BREUSCH_PAGAN_GODFREY Syntax Elements
TD_BREUSCH_PAGAN_GODFREY Input
TD_BREUSCH_PAGAN_GODFREY Output
TD_BREUSCH_PAGAN_GODFREY Example
TD_CUMUL_PERIODOGRAM
TD_CUMUL_PERIODOGRAM Syntax
TD_CUMUL_PERIODOGRAM Syntax Elements
TD_CUMUL_PERIODOGRAM Input
TD_CUMUL_PERIODOGRAM Output
TD_CUMUL_PERIODOGRAM Example
TD_DICKEY_FULLER
TD_DICKEY_FULLER Syntax
TD_DICKEY_FULLER Syntax Elements
TD_DICKEY_FULLER Input
TD_DICKEY_FULLER Output
TD_DICKEY_FULLER Example
TD_DURBIN_WATSON
TD_DURBIN_WATSON Syntax
TD_DURBIN_WATSON Syntax Elements
TD_DURBIN_WATSON Input
TD_DURBIN_WATSON Output
TD_DURBIN_WATSON Examples
TD_FITMETRICS
TD_FITMETRICS Syntax
TD_FITMETRICS Syntax Elements
TD_FITMETRICS Input
TD_FITMETRICS Output
TD_FITMETRICS Examples
TD_GOLDFELD_QUANDT
TD_GOLDFELD_QUANDT Syntax
TD_GOLDFELD_QUANDT Syntax Elements
TD_GOLDFELD_QUANDT Input
TD_GOLDFELD_QUANDT Output
TD_GOLDFELD_QUANDT Example
TD_PORTMAN
TD_PORTMAN Syntax
TD_PORTMAN Syntax Elements
TD_PORTMAN Input
TD_PORTMAN Output
TD_PORTMAN Examples
TD_SELECTION_CRITERIA
TD_SELECTION_CRITERIA Syntax
TD_SELECTION_CRITERIA Syntax Elements
TD_SELECTION_CRITERIA Input
TD_SELECTION_CRITERIA Output
TD_SELECTION_CRITERIA Examples
TD_SIGNIF_PERIODICITIES
TD_SIGNIF_PERIODICITIES Syntax
TD_SIGNIF_PERIODICITIES Syntax Elements
TD_SIGNIF_PERIODICITIES Input
TD_SIGNIF_PERIODICITIES Output
TD_SIGNIF_PERIODICITIES Example
TD_SIGNIF_RESIDMEAN
TD_SIGNIF_RESIDMEAN Syntax
TD_SIGNIF_RESIDMEAN Syntax Elements
TD_SIGNIF_RESIDMEAN Input
TD_SIGNIF_RESIDMEAN Output
TD_SIGNIF_RESIDMEAN Example
TD_WHITES_GENERAL
TD_WHITES_GENERAL Syntax
TD_WHITES_GENERAL Syntax Elements
TD_WHITES_GENERAL Input
TD_WHITES_GENERAL Output
TD_WHITES_GENERAL Example
Model Preparation and Parameter Estimation Functions
Creating an ARIMA Model
TD_ACF
TD_ACF Syntax
TD_ACF Syntax Elements
TD_ACF Input
TD_ACF Output
TD_ACF Examples
TD_ARIMAESTIMATE
TD_ARIMAESTIMATE Syntax
TD_ARIMAESTIMATE Syntax Elements
TD_ARIMAESTIMATE Input
TD_ARIMAESTIMATE Output
TD_ARIMAESTIMATE Examples
TD_ARIMAVALIDATE
TD_ARIMAVALIDATE Syntax
TD_ARIMAVALIDATE Syntax Elements
TD_ARIMAVALIDATE Input
TD_ARIMAVALIDATE Output
TD_ARIMAVALIDATE Examples
TD_DIFF
TD_DIFF Syntax
TD_DIFF Syntax Elements
TD_DIFF Input
TD_DIFF Output
TD_DIFF Examples
TD_LINEAR_REGR
TD_LINEAR_REGR Syntax
TD_LINEAR_REGR Syntax Elements
TD_LINEAR_REGR Input
TD_LINEAR_REGR Output
TD_LINEAR_REGR Examples
TD_MULTIVAR_REGR
TD_MULTIVAR_REGR Syntax
TD_MULTIVAR_REGR Syntax Elements
TD_MULTIVAR_REGR Input
TD_MULTIVAR_REGR Output
TD_MULTIVAR_REGR Examples
TD_PACF
TC_PACF Syntax
TC_PACF Syntax Elements
TD_PACF Input
TD_PACF Output
TD_PACF Example
TD_POWERTRANSFORM
TD_POWERTRANSFORM Syntax
TD_POWERTRANSFORM Syntax Elements
How BACK_TRANSFORM, P, B, and LAMBDA Determine Transform Equation
TD_POWERTRANSFORM Input
TD_POWERTRANSFORM Output
TD_POWERTRANSFORM Example
TD_SEASONALNORMALIZE
TD_SEASONALNORMALIZE Syntax
TD_SEASONALNORMALIZE Syntax Elements
TD_SEASONALNORMALIZE Input
TD_SEASONALNORMALIZE Output
TD_SEASONALNORMALIZE Examples
TD_SMOOTHMA
TD_SMOOTHMA Syntax
TD_SMOOTHMA Syntax Elements
TD_SMOOTHMA Input
TD_SMOOTHMA Output
TD_SMOOTHMA Examples
TD_UNDIFF
TD_UNDIFF Syntax
TD_UNDIFF Syntax Elements
TD_UNDIFF Input
TD_UNDIFF Output
TD_UNDIFF Example
TD_UNNORMALIZE
TD_UNNORMALIZE Syntax
TD_UNNORMALIZE Syntax Elements
TD_UNNORMALIZE Input
TD_UNNORMALIZE Output
TD_UNNORMALIZE Example
Series Forecasting Functions
TD_ARIMAFORECAST
TD_ARIMAFORECAST Syntax
TD_ARIMAFORECAST Syntax Elements
TD_ARIMAFORECAST Input
TD_ARIMAFORECAST Output
TD_ARIMAFORECAST Examples
TD_DTW
TD_DTW Syntax
TD_DTW Syntax Elements
TD_DTW Input
TD_DTW Output
TD_DTW Examples
TD_HOLT_WINTERS_FORECASTER
TD_HOLT_WINTERS_FORECASTER Syntax
TD_HOLT_WINTERS_FORECASTER Syntax Elements
TD_HOLT_WINTERS_FORECASTER Input
TD_HOLT_WINTERS_FORECASTER Output
TD_HOLT_WINTERS_FORECASTER Examples
TD_KALMAN_FORECASTER
TD_KALMAN_FORECASTER Syntax
TD_KALMAN_FORECASTER Required Syntax Elements
TD_KALMAN_FORECASTER Optional Syntax Elements
TD_KALMAN_FORECASTER Input
TD_KALMAN_FORECASTER Output
TD_KALMAN_FORECASTER Examples
TD_MAMEAN
TD_MAMEAN Syntax
TD_MAMEAN Syntax Elements
TD_MAMEAN Input
TD_MAMEAN Output
TD_MAMEAN Examples
TD_SIMPLEEXP
TD_SIMPLEEXP Syntax
TD_SIMPLEEXP Syntax Elements
TD_SIMPLEEXP Input
TD_SIMPLEEXP Output
TD_SIMPLEEXP Examples
TD_SMOOTHMA_FORECASTER
TD_SMOOTHMA_FORECASTER Syntax
TD_SMOOTHMA_FORECASTER Required Syntax Elements
TD_SMOOTHMA_FORECASTER Optional Syntax Elements
TD_SMOOTHMA_FORECASTER Input
TD_SMOOTHMA_FORECASTER Output
TD_SMOOTHMA_FORECASTER Examples
Temporal and Spatial Functions
TD_CONVOLVE
TD_CONVOLVE Syntax
TD_CONVOLVE Syntax Elements
TD_CONVOLVE Input
TD_CONVOLVE Output
TD_CONVOLVE Example
TD_CONVOLVE2
TD_CONVOLVE2 Syntax
TD_CONVOVLE2 Syntax Elements
TD_CONVOLVE2 Input
TD_CONVOLVE2 Output
TD_CONVOLVE2 Examples
TD_DFFT
TD_DFFT Syntax
TD_DFFT Syntax Elements
TD_DFFT Input
TD_DFFT Output
TD_DFFT Example
TD_DFFT2
TD_DFFT2 Syntax
TD_DFFT2 Syntax Elements
TD_DFFT2 Input
TD_DFFT2 Output
TD_DFFT2 Example
TD_DFFTCONV
TD_DFFTCONV Syntax
TD_DFFTCONV Syntax Elements
TD_DFFTCONV Input
TD_DFFTCONV Output
TD_DFFTCONV Example
TD_DFFT2CONV
TD_DFFT2CONV Syntax
TD_DFFT2CONV Syntax Elements
TD_DFFT2CONV Input
TD_DFFT2CONV Output
TD_DFFT2CONV Example
TD_GENSERIES4SINUSOIDS
TD_GENSERIES4SINUSOIDS Syntax
TD_GENSERIES4SINUSOIDS Syntax Elements
TD_GENSERIES4SINUSOIDS Input
TD_GENSERIES4SINUSOIDS Output
TD_GENSERIES4SINUSOIDS Example
TD_IDFFT
TD_IDFFT Syntax
TD_IDFFT Syntax Elements
TD_IDFFT Input
TD_IDFFT Output
TD_IDFFT Examples
TD_IDFFT2
TD_IDFFT2 Syntax
TD_IDFFT2 Syntax Elements
TD_IDFFT2 Input
TD_IDFFT2 Output
TD_IDFFT2 Example
TD_LINESPEC
TD_LINESPEC Syntax
TD_LINESPEC Syntax Elements
TD_LINESPEC Input
TD_LINESPEC Output
TD_LINESPEC Examples
TD_POWERSPEC
TD_POWERSPEC Syntax
TD_POWERSPEC Syntax Elements
TD_POWERSPEC Input
TD_POWERSPEC Output
TD_POWERSPEC Examples
Mathematic Operators and Functions
Mathematic Operators
Mathematic Functions
Formula Rules
UAF Analytic Functions Examples
API Integration Guide for Cloud Machine Learning
Teradata Partner API
Welcome to Teradata API Integration
Key Feature Additions and Changes
Amazon Web Services
Software Compatibility and Dependencies
Getting Ready to Use Teradata API Integration for AWS
AWS Credentials
AWS Endpoints
API_Request In-database Function
API_Request In-database Function Installation
API_Request In-database Function Syntax
API_Request In-database Function Syntax Elements
API_Request In-database Function with Amazon SageMaker
API_Request In-database Function Input
API_Request In-database Function Output Schema
API_Request In-database Function Usage
API_Request In-database Function with Amazon Forecast
API_Request In-database Function Input
API_Request In-database Function Output Schema
API_Request In-database Function Usage
Troubleshooting for API_Request
Limitations and Considerations for API_Request
teradataml Extension
teradataml SageMaker Extension Library Installation
create_tdapi_context Method
remove_tdapi_context Method
TDApiClient Class
TDApiClient.deploy Method
TDApiClient.fit Method
TDPredictor.predict Method
TDPredictor.from_predictor Method
Property cloudObj
TDApiClient.API_Request
Use Cases
Use SageMaker PyTorch Estimator with tdapiclient
Use SageMaker SKLearn Estimator with tdapiclient
Use SageMaker Chainer Estimator with tdapiclient
Use SageMaker KMeans Estimator with tdapiclient
Use SageMaker TensorFlow Estimator with tdapiclient
Use SageMaker RandomCutForest with tdapiclient
Use SageMaker XGBoost Estimator with tdapiclient
Use SageMaker kNN with tdapiclient
Use SageMaker LDA with tdapiclient
Use SageMaker PCA with tdapiclient
Use SageMaker Linear Learner with tdapiclient
Azure Machine Learning
Software Compatibility and Dependencies
Getting Ready to Use Teradata API Integration for Azure Machine Learning
Azure Machine Learning Endpoints
API_Request In-database Function
API_Request In-database Function Installation
API_Request In-database Function Syntax
API_Request In-database Function Syntax Elements
API_Request In-database Function Input
API_Request In-database Function Output Schema
API_Request In-database Function Usage
teradataml Extension
create_tdapi_context Method
remove_tdapi_context Method
TDApiClient Class
fit() Method - Training Azure Machine Learning Model
deploy() Method - Deploying Azure Machine Learning Model
TDAzurePredictor.predict Method
TDAzurePredictor.from_predictor Method
BYOMPredictor Class
BYOMPredictor.predict Method
TDApiClient.API_Request
Use Cases
Google Vertex AI
Software Compatibility and Dependencies
Getting Ready to Use Teradata API Integration for Google Vertex AI
Google Vertex AI Endpoints
API_Request In-database Function
API_Request In-database Function Installation
API_Request In-database Function Syntax
API_Request In-database Function Syntax Elements
API_Request In-database Function Input
API_Request In-database Function Output Schema
API_Request In-database Function Usage
teradataml Extension
create_tdapi_context Method
remove_tdapi_context Method
TDApiClient Class
TrainingJob.fit Method
TrainingJob.deploy Method
TDApiClient.API_Request
Use Cases
OpenAI and Azure OpenAI
Software Compatibility and Dependencies
Getting Ready to Use Teradata API Integration with OpenAI or Azure OpenAI
API_Request In-database Function
API_Request In-database Function Installation
API_Request In-database Function Syntax
API_Request In-database Function Syntax Elements
API_Request In-database Function Input
API_Request In-database Function Output Schema
API_Request In-database Function Usage
teradataml Extension
TDApiClient.API_Request
Use Cases
Amazon Bedrock
Software Compatibility and Dependencies
Getting Ready to Use Teradata API Integration with Amazon Bedrock
Amazon Bedrock Endpoints
API_Request In-database Function
API_Request In-database Function Installation
API_Request In-database Function Syntax
API_Request In-database Function Syntax Elements
API_Request In-database Function Input
API_Request In-database Function Output Schema
API_Request In-database Function Usage
teradataml Extension
TDApiClient.API_Request
Example Prerequisites
nPath Visualization
Create a New Connection for nPath Visualization
Access the nPath Function
The nPath Function Cards
Generate a Query using nPath
nPath Event Table Structure
Analyze the Tree Diagram
Analyze the Sankey Chart
In-DB Analytic Functions Explorer
Open the In-DB Analytic Functions Explorer
Use the In-DB Analytic Functions Explorer
Use Build Query to Run an Analytic Query
Create a View with the Query Results
Save the Build Query Results: Permanent or Volatile Table
Character Shorthand Notation Used in This Document
How to Read Syntax
SecondaryColumn
Name of the input table column that contains the text. This field is applicable for the token2token-similarity and doc2doc-similarity operations only.
Accumulate
List of columns to be added to the output from the input table. This is not applicable with the token-embedding operation.
Operation
Operation to be performed on the data. Options are: token-embedding: Emits vectors to all tokens in the column.
doc-embedding: Vectorizes each token in the document and combines them.
token2token-similarity: Computes the similarity between tokens and quantifies the result value.
doc2doc-similarity: Computes the similarity between documents and quantifies the result value.
Default value: token-embedding
RemoveStopWords
All stop words present in the input table text are removed before any operation is performed. Applicable to all operations except token2token-similarity. Default is False.
ConvertToLowerCase
All operations are performed after converting input table text to lowercase letters. Default is True.
StemTokens
Converts word to its root word in the input table, such as converting going to go. Default is False.