Explain the difference between a test set and a validation set?
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Answer / Charan Singh
A Test Set is used to evaluate the performance of a machine learning model on new, unseen data. It is usually separated from the training set and held out for testing after the model has been trained. A Validation Set, on the other hand, is used during the training process to tune hyperparameters and select the best model. It is often split from the training set but may be combined with it during cross-validation.
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