# What makes a machine learning algorithm a low variance one or a high variance one?

Some examples of low-variance machine learning algorithms include linear regression, linear discriminant analysis, and logistic regression.

Examples of high-variance machine learning algorithms include decision trees, k-nearest neighbors, and support vector machines.

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What makes a machine learning algorithm a low variance one or a high variance one? For example, why do decision trees, k-NNs and SVMs have high variance?