All 7 Cross-Validation Techniques questions
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What is Cross-Validation Techniques

Beginner

Answer

Cross validation is a technique for testing a machine learning model by splitting the data into several parts and training and testing the model multiple times on different combinations of those parts.
Real-world example A team building a disease prediction model uses five fold cross validation to make sure their reported accuracy is stable and not just the result of one favorable data split.

Common follow-ups: What is a validation set, What is overfitting, What is model evaluation

Machine Learning Fundamentals Deep Learning Supervised & Unsupervised Learning
All 7 Cross-Validation Techniques questions