# Why KNN, Decision Trees, etc have a high variance?

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?