April 2024
Intermediate to advanced
264 pages
6h 10m
English
Content preview from Machine Learning Q and AI
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28THE K IN K-FOLD CROSS-VALIDATION
k-fold cross-validation is a common choice for evaluating machine learning classifiers because it lets us use all training data to simulate how well a machine learning algorithm might perform on new data. What are the advantages and disadvantages of choosing a large k?
We can think of k-fold cross-validation as a workaround for model evaluation when we have limited data. In machine learning model evaluation, we care about the generalization performance of our model, that is, how well it performs on new data. In k-fold cross-validation, we use the training data for model selection and evaluation by partitioning ...
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