Cross Validation: Essential Techniques for Machine Learning Models

Learn the fundamentals of cross validation, a crucial method for evaluating and selecting the best machine learning models. This video explains k fold, stratified k fold, leave one out, and repeated k fold cross validation techniques using a simple dataset. Discover how these techniques help in achieving reliable and robust predictions for models like k nearest neighbors, decision trees, and logistic regression. Perfect for beginners looking to boost their model evaluation skills.

00:00 Introduction to Cross Validation
00:13 Understanding the Dataset
00:47 What is Cross Validation?
01:18 K-Fold Cross Validation Explained
02:23 Stratified K-Fold Cross Validation
03:22 Leave-One-Out Cross Validation
03:50 Repeated K-Fold Cross Validation
04:17 Conclusion and Key Takeaways

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