Python Transform

This Component transforms values of the user selected columns to normalized values by standardizing them across their mean values. The Component uses the Python Extension to perform the normalization with the Python Class “Standard Scaler preprocessing” in the Scikit learn library (https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.StandardScaler.html). This Component outputs the normalized values along with the Python Pickled Object that contains the parameters used for normalisation.

DATA INPUT REQUIREMENTS
- The input data should have numerical columns which can be transformed.

Options

One hot encoding of Target column
Check the box, if the Target column has to be one hot encoded
Feature Column Selection:
Select the columns which should be used for transformation. Domain accepted: Number (Integer), Number (double), Number (long)
Select the Target column:
Select the Target column that would be appended to the output along with the transformed columns.

Input Ports

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Input Data.

Output Ports

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Transformed columns as per the user selection in the configuration panel.
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Python Pickle Object which can be used to normalise the data, based on the normalisation parameters used in this Component.

Nodes

Extensions

Links