Documentation Index
Fetch the complete documentation index at: https://docs.clickml.app/llms.txt
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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 |
| 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.
