Which model selection technique involves dividing the dataset into multiple subs

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Question: Which model selection technique involves dividing the dataset into multiple subsets for training and validation?

Options:

Correct Answer: Cross-validation

Solution:

Cross-validation involves dividing the dataset into multiple subsets to validate the model\'s performance on different data.

Which model selection technique involves dividing the dataset into multiple subsets for training and validation?

Which model selection technique involves dividing the dataset into multiple subsets for training and validation?

Step 1: Understand that model selection is about choosing the best model for your data.
Step 2: Learn that cross-validation is a technique used in model selection.
Step 3: Know that in cross-validation, you divide your dataset into multiple parts or subsets.
Step 4: Use some of these subsets to train the model and others to test or validate the model's performance.
Step 5: Repeat this process several times to ensure the model is tested on different data each time.

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