Glossary · Phase 3 · Machine learning
Training set
The examples a model learns from.
Try it now
Each set answers one question. Mixing their jobs is how inflated scores happen.
Learn it properly
Train, validation and test sets · Hold data back so you can trust your results. About 25 minutes.
Other terms from the same lesson
- data leakage: When information from the test data sneaks into training, so the model looks better than it really is on new data.
- stratified split: Splitting data so each part keeps the same mix of classes as the whole, for example the same share of churners in train and test.
- test set: Examples kept aside until the very end to give an honest score on unseen data.
- validation set: Held-back examples used to compare and tune models while you work.
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