What is the purpose of cross-validation in machine learning?
Practice Questions
1 question
Q1
What is the purpose of cross-validation in machine learning?
To increase the size of the training dataset
To assess how the results of a statistical analysis will generalize to an independent dataset
To reduce the complexity of the model
To improve the speed of training
Cross-validation is used to assess how well a model generalizes to an independent dataset by partitioning the data into training and validation sets.
Questions & Step-by-step Solutions
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Q
Q: What is the purpose of cross-validation in machine learning?
Solution: Cross-validation is used to assess how well a model generalizes to an independent dataset by partitioning the data into training and validation sets.
