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How can you choose a classifier based on a training set size?

Choosing a classifier

If the training set is small, high bias / low variance models (e.g. Naive Bayes) tend to perform better because they are less likely to overfit.

If the training set is large, low bias / high variance models (e.g. Logistic Regression) tend to perform better because they can reflect more complex relationships.

Unsupervised Learning