What is the difference between training and testing datasets in Machine Learning?
- Training for clustering; Testing for regression
- Training for labeling; Testing for predicting
- Training used to evaluate; Testing used to predict
- Training used to learn patterns; Testing used to evaluate performance
In Machine Learning, the training dataset is used for the model to learn patterns, and the testing dataset is used to evaluate the model's performance on unseen data.
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