Data Transformation component - ClickML Studio

The Data Transformation component applies element-wise mathematical functions to numerical columns — useful for fixing skewed distributions before training.

Configuration

Option	Description
Method	The transformation to apply (see table below).
Columns	Columns to transform. Supports `All Numerical Features`.
Threshold	Used only by the `Binarize` method. Values above this threshold become 1, values at or below become 0.

Methods

Method	Formula	Use case
Log	`log(x)`	Right-skewed distributions (values must be positive)
Log1p	`log(1 + x)`	Right-skewed distributions that include zero
Square Root	`√x`	Moderate right skew
Cube Root	`∛x`	Handles negative values
Square	`x²`	Amplify differences for small values
Cube	`x³`	Amplify differences more aggressively
Exponential	`eˣ`	Left-skewed distributions
Box-Cox	Power transform — finds optimal lambda automatically	General normalization (positive values only)
Yeo-Johnson	Like Box-Cox but handles zero and negative values	General normalization
Binarize	`1 if x > threshold else 0`	Converting continuous features to binary flags

Input / Output

	Type
Input	DataFrame
Output	DataFrame