Feature Engineering Transform Functions - Teradata Vantage
Teradata® VantageCloud Lake
- Deployment
- VantageCloud
- Edition
- Lake
- Product
- Teradata Vantage
- Published
- January 2023
- ft:locale
- en-US
- ft:lastEdition
- 2024-12-11
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- 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_SMOTE
- Implements SMOTE and three variations (ADASYN, Borderline, and SMOTE-NC) to sample from datasets, border groups, or mixed datasets.
- 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.