How do I use cross-validation in machine learning?

How do I use cross-validation in machine learning?

Cross-validation is a technique to assess how the results of a statistical analysis will generalize to an independent dataset. Would you like to know about different types of cross-validation?

Yes, what are the different types?

The most common types are k-fold cross-validation, stratified k-fold, and leave-one-out cross-validation. Do you want details on any specific type?

Can you explain k-fold cross-validation?

Sure! In k-fold cross-validation, the dataset is divided into 'k' subsets. The model is trained on 'k-1' subsets and tested on the remaining one. This process is repeated 'k' times, with each subset used as the test set once.

How do I implement it in Python?

You can use libraries like scikit-learn. The KFold class allows you to easily implement k-fold cross-validation. Would you like a code example?