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Train/test split

concept · part of Machine Learning & Data

A technique to separate data into training and test sets to evaluate model performance on unseen data.

The dataset is split into training and test sets using sklearn's train_test_split with a test size of 0.2 and random_state=42 for reproducibility. The training set is used to fine-tune the model, and the test set is used for evaluation.

train_data, test_data = train_test_split(data, test_size=0.2, random_state=42)

Common parameters: test_size (proportion of test set), random_state (seed for reproducibility).

Connections

• Prerequisite of Accuracy

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