Cross Validation

What is cross validation?

Cross-validation is a more robust method to evaluate the model's performance. It involves splitting the data into k subsets (folds) and performing the training and testing k times, each time using a different fold as the test set and the remaining folds as the training set. This provides multiple performance estimates, reducing the risk of overfitting.

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Types of Cross-Validation

• k-Fold Cross-Validation

• Stratified k-Fold Cross-Validation

• Leave-One-Out Cross-Validation (LOOCV)

• Time Series Cross-Validation

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