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K-Fold Cross Validation Explained by Zainab Jutt234 is a document available to read on EtoBox.
What is K-Fold Cross Validation Explained about?
K-fold cross validation is a resampling procedure used to evaluate machine learning models on a limited data sample. It involves splitting the sample into k groups, using k-1 for training and 1 for testing, and repeating this process k times while rotating the test set. This provides a mean validation accuracy and expected performance metric for the model.
- Author
- Zainab Jutt234
- Language
- EN