What is Cross-Validation?

1.	What is Cross-Validation?
Answer» Cross-Validation is a Statistical technique used for improving a model’s PERFORMANCE. Here, the model will be TRAINED and tested with rotation using different samples of the training dataset to ensure that the model performs WELL for unknown data. The training data will be SPLIT into various groups and the model is run and VALIDATED against these groups in rotation. The most commonly used techniques are: K- Fold method Leave p-out method Leave-one-out method Holdout method

Answer»

Cross-Validation is a Statistical technique used for improving a model’s PERFORMANCE. Here, the model will be TRAINED and tested with rotation using different samples of the training dataset to ensure that the model performs WELL for unknown data. The training data will be SPLIT into various groups and the model is run and VALIDATED against these groups in rotation.

The most commonly used techniques are:

K- Fold method
Leave p-out method
Leave-one-out method
Holdout method

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What is Cross-Validation?

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