TD_TrainTestSplit

Fast path function to split input dataset into train dataset and test dataset as per mentioned trainSize and testSize as arguments

Options

IDColumn: Specify the name of the InputTable column that contains the unique value for to get the deterministic row in each function call.
seed: Specifies the seed value for the function to select the rows for train and test randomly . The seed must be a NUMERIC value in the range [1, 2147483647]. The seed is used in function for uniform real distribution to randomly select the rows for train and test dataset.
StratifyColumn: Specify the name of the InputTable column that contains the stratify classes of the TD_TrainTestSplit.
Output Schema: Output Schema, if Volatile is true then use user login as the schema.
Output Table: Output Table
VAL Location: VAL Location
Volatile: Specifies whether the table should be a VOLATILE table. If true, then the table is automatically deleted, otherwise it is users responsibility to remove or clean it up for space.
testSize: Specifies the testSize value for the function to select the number of rows for test table . The testSize must be a FLOAT value in the range (0.0, 1.0). The default value for the testSize is 0.25 .
trainSize: Specifies the trainSize value for the function to select the number of rows for train table . The trainSize must be a FLOAT value in the range (0.0, 1.0). The default value for the trainSize is 0.75 .

: Connection to a Teradata Database Instance
: Specifies the name of the table that contains input dataset on which split to be performed.