Optional Syntax Elements for TD_OneClassSVM - Analytics Database
Database Analytic Functions
Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Analytics Database
Release Number
17.20
Published
June 2022
ft:locale
en-US
ft:lastEdition
2025-04-01
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Product Category
Teradata Vantage™
Introduction to Analytics Database Analytic Functions
Changes and Additions
Analytics 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 Database Analytic Functions
BC/BCE Timestamps
Workload Management Configuration for Analytics 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
Optional Syntax Elements for TD_GetRowsWithoutMissingValues
TD_GetRowsWithoutMissingValues Input
TD_GetRowsWithoutMissingValues Output
Example: How to Use TD_GetRowsWithoutMissingValues
TD_OutlierFilterFit
TD_OutlierFilterFit Syntax
TD_OutlierFilterFit Syntax Elements
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
Required Syntax Elements for Unpack
Optional Syntax Elements for Unpack
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
Weighted Moving Average
Triangular Moving Average
Simple Moving Average
Modified Moving Average
Exponential Moving Average
Cumulative 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
Optional Syntax Elements for TD_PolynomialFeaturesFit
TD_PolynomialFeaturesFit Input
TD_PolynomialFeaturesFit Output
Example: How to Use TD_PolynomialFeaturesFit
TD_PolynomialFeaturesTransform
TD_PolynomialFeaturesTransform Syntax
Required Syntax Elements for TD_PolynomialFeaturesTransform
Optional Syntax Elements for TD_PolynomialFeaturesTransform
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_TargetEncodingFit
TD_TargetEncodingFit Syntax
TD_TargetEncodingFit Syntax Elements
TD_TargetEncodingFit Input
TD_TargetEncodingFit Output
TD_TargetEncodingFit Examples
TD_TargetEncodingFit Usage Notes
TD_TargetEncodingTransform
TD_TargetEncodingTransform Syntax
TD_TargetEncodingTransform Syntax Elements
TD_TargetEncodingTransform Input
TD_TargetEncodingTransform Output
TD_TargetEncodingTransform Examples
TD_TargetEncodingTransform Usage Notes
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
Optional Syntax Elements for TD_NumApply
TD_NumApply Input
TD_NumApply Output
TD_NumApply Usage Notes
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
Required Syntax Elements for TD_StrApply
Optional Syntax Elements for TD_StrApply
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
Using Partition by Any
Using Partition by Key (Micromodeling)
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_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
TD_KNN
TD_KNN Usage Notes
TD_KNN Syntax
Required Syntax Elements for TD_KNN
Optional Syntax Elements for TD_KNN
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
Example: TD_VectorDistance Using Euclidean, Manhattan, and Cosine
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
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_KMeansPredict
TD_KMeansPredict Syntax
Required Syntax Elements for TD_KMeansPredict
Optional Syntax Elements for TD_KMeansPredict
TD_KMeansPredict Input
TD_KMeansPredict Output
Example: How to Use the k-means Algorithm
Examples: How to Use 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_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_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_RegressionEvaluator
TD_RegressionEvaluator Syntax
Required Syntax Elements for TD_RegressionEvaluator
Optional Syntax Elements in TD_RegressionEvaluator
TD_RegressionEvaluator Input
TD_RegressionEvaluator Output
TD_RegressionEvaluator Usage Notes
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_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_Ngramsplitter
TD_Ngramsplitter Usage Notes
TD_Ngramsplitter Syntax
Required Syntax Elements for TD_Ngramsplitter
Optional Syntax Elements for TD_Ngramsplitter
TD_Ngramsplitter Input
TD_Ngramsplitter Output
Examples: How to Use TD_Ngramsplitter
TD_Ngramsplitter Examples Input
Example: Omit Accumulate
Example: Specify Accumulate
Examples: Using Regular Expressions with TD_Ngramsplitter
Input
Example 1: Range A-Z and a-z
Example 2: Remove all Punctuation Marks
Example 3: Remove all Punctuation Marks and Reset at Punctuation
Example 4: Remove all Punctuation Marks and Delimiter at Punctuation
Example 5: Remove all Punctuation Marks from Unicode Data
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_SentimentExtractor
TD_SentimentExtractor Syntax
Required Syntax Elements for TD_SentimentExtractor
Optional Syntax Elements for TD_SentimentExtractor
TD_SentimentExtractor Input
TD_SentimentExtractor Output
TD_SentimentExtractor Usage Notes
Examples: How to Use TD_SentimentExtractor
TD_TextMorph
TD_TextMorph Syntax
Required Syntax Elements for TD_TextMorph
Optional Syntax Elements for TD_TextMorph
TD_TextMorph Input
TD_TextMorph Output
Examples: How to Use TD_TextMorph
TD_TextMorph Examples Input
Example 1: TD_TextMorph with SingleOuptut set to 'True'
Example 2: TD_TextMorph with SingleOuptut set to 'False'
Example 3: TD_TextMorph with POS Argument Specified and SingleOuptut Set to 'False'
Example 4: TD_TextMorph with POS Argument Specified and SingleOuptut Set to 'True'
Example 5: TD_TextMorph with POSTagColumn Argument Specified
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 Usage Notes
Examples: How to Use TD_TextParser
Example 1: Using TD_TextParser with StopWords Table
Example 2: Using TD_TextParser to Get Token Frequency and List of Positions
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
Example: How to Use TD_ChiSq
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_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
How to Read Syntax
Additional Information
Teradata Links
Related Documentation
OUT clause
Accepts the MetaInformationTable clause.
MaxIterNum
Specify the maximum number of iterations (minibatches) over the training data batches. Value is a positive integer less than 10,000,000. Default value is 300.
BatchSize
Specify the number of observations (training samples) processed in a single minibatch per AMP. A value of 0 or higher than the number of rows on an AMP processes all rows on the AMP, such that the entire dataset is processed in a single iteration, and the algorithm becomes Gradient Descent. You must specify a non-negative integer. Default value is 10.
RegularizationLambda
Specify the amount of regularization to be added. The higher the value, stronger the regularization. It is also used to compute learning rate when learning rate is set to optimal. Must be a non-negative float value. A value of 0 means no regularization. Default is 0.02.
Alpha
Specify the Elasticnet parameter for penalty computation. It is only effective when RegularizationLambda is greater than 0. The value represents the contribution ratio of L1 in the penalty. A value of 1.0 indicates L1 (LASSO) only, a value of 0 indicates L2 (Ridge) only, and a value between is a combination of L1 and L2. Value is a float value between 0 and 1. Default is 0.15.
IterNumNoChange
Specify the number of iterations (minibatches) with no improvement in loss including the tolerance to stop training. A value of 0 indicates no early stopping and the algorithm continues until MaxIterNum iterations are reached. Value is a non-negative integer. Default is 50.
Tolerance
Specify the stopping criteria in terms of loss function improvement. Applicable when IterNumNoChange is greater than 0. Value is a positive integer. Default is 0.001.
Intercept
Specify whether to estimate the intercept based on whether data is already centered. Default is true.
LearningRate
Specify the learning rate algorithm. Learning rates are:Constant
InvTime
Optimal
Adaptive
Default is invtime for Gaussian, optimal for Binomial.
InitialEta
Specify the initial value of eta for learning rate. For LearningRate set to constant, this value is the learning rate for all iterations. Value is numeric. Default is 0.05.
DecayRate
Specify the decay rate for learning rate. Only applicable for learning rates invtime and adaptive. Value is numeric. Default is 0.25.
DecaySteps
Specify the number of iterations without decay for the adaptive learning rate. The learning rate changes by decay rate after this many iterations. Value is integer. Default is 5.
Momentum
Specify the value to use for momentum learning rate optimizer. A larger value indicates higher momentum contribution. A value of 0 means momentum optimizer is disabled. For a good momentum contribution, a value between 0.6-0.95 is recommended. Value is a non-negative float between 0 and 1. Default is 0.
Nesterov
Specify whether to apply Nesterov optimization to Momentum optimizer. Only applicable when Momentum is greater than 0. Default is false.
LocalSGDIterations
Specify the number of local iterations to be used for Local SGD algorithm. A value of 0 implies Local SGD is disabled. A value higher than 0 enables Local SGD and multiple, equal to the value supplied by the user. With Local SGD algorithm, the recommended values for arguments are:LocalSGDIterations: 10
MaxIterNum: 100
BatchSize: 50
IterNumNoChange: 5
Value is a positive integer. Default is 0.