Train-Test Split component - ClickML Studio

The Train-Test Split component divides your DataFrame into features (X) and target (y) and then splits them into training and test portions. Its output handles connect directly to model and evaluation components.

Configuration

Option	Description	Default
Target Column	The column the model should learn to predict	—
Split Mode	How to divide the data (see below)	Train/Test
Test Size	Fraction of data reserved for the test set	`0.2` (20%)
Validation Size	Fraction reserved for validation (Train/Val/Test mode only)	`0.1` (10%)
Random State	Seed for reproducibility	`42`
Stratify	Keep class proportions equal across splits (classification only)	Off

Split modes

Mode	Output handles
No Split (Full Data)	`X`, `y`
Train/Test	`X Train`, `Y Train`, `X Test`, `Y Test`
Train/Validation/Test	`X Train`, `Y Train`, `X Val`, `Y Val`, `X Test`, `Y Test`

Input / Output

	Type
Input	DataFrame
Output	Split Data (separate handles per set)

Enable Stratify for imbalanced classification datasets to ensure every split has a representative distribution of each class.