Feature Engineering Transform Functions - Analytics Database

Database Analytic Functions

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Analytics Database
Release Number
17.20
Published
June 2022
Language
English (United States)
Last Update
2024-10-04
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Product Category
Teradata Vantageā„¢
Antiselect
AntiSelect returns all columns except those specified.
TD_BinCodeFit
Converts numeric data to categorical data by binning the numeric data into multiple numeric bins (intervals).
TD_BinCodeTransform
Transforms input table columns from the BinCodeFit function output.
TD_ColumnTransformer
Transforms the input table columns in a single operation.
TD_FunctionFit
Determines whether specified numeric transformations can be applied to specified input columns.
TD_FunctionTransform
Applies numeric transformations to input columns.
TD_NonLinearCombineFit
Returns the target columns and a specified formula which uses the non-linear combination of existing features.
TD_NonLinearCombineTransform
Generates the values of the new feature using the specified formula from the TD_NonLinearCombineFit function output.
TD_OneHotEncodingFit
Outputs a table of attributes and categorical values to the TD_OneHotEncodingTransform function.
TD_OneHotEncodingTransform
Encodes specified attributes and categorical values as one-hot numeric vectors using the output from the TD_OneHotEncodingFit function.
TD_OrdinalEncodingFit
Encodes specified attributes and categorical values as one-hot numeric vectors using the output from the TD_OneHotEncodingFit function.
TD_OrdinalEncodingTransform
Maps the categorical value to a specified ordinal value using the TD_OrdinalEncodingFit output.
TD_Pivoting
Pivots the data, that is, changes the data from sparse to dense format.
TD_PolynomialFeaturesFit
Stores all the specified values in the argument in a tabular format.
TD_PolynomialFeaturesTransform
Extracts values of arguments from the output of the TD_PolynomialFeaturesFit function and generates a feature matrix of all polynomial combinations of the features.
TD_RandomProjectionFit
Returns a random projection matrix based on the specified arguments.
TD_RandomProjectionMinComponents
Calculates the minimum number of components required for applying RandomProjection on the given dataset for the specified epsilon(distortion) parameter value.
TD_RandomProjectionTransform
Converts the high-dimensional input data to a lower-dimensional space using the TD_RandomProjectionFit function output.
TD_RowNormalizeFit
Outputs a table of parameters and specified input columns to TD_RowNormalizeTransform which normalizes the input columns row-wise.
TD_RowNormalizeTransform
Normalizes the input columns row-wise using the output of the TD_RowNormalizeFit function.
TD_ScaleFit
Outputs a table of statistics to the TD_ScaleTransform function.
TD_ScaleTransform
Scales the specified input table columns using the output of the TD_ScaleFit function.
TD_TargetEncodingFit
Takes the InputTable and a CategoricalTable as input and generates the required hyperparameters to be used by the TD_TargetEncodingTransform function for encoding the categorical values.
TD_TargetEncodingTransform
Takes the InputTable and a FitTable generated by TD_TargetEncodingFit for encoding the categorical values.
TD_Unpivoting
Unpivots the data, that is, changes the data from dense format to sparse format.