Bias are the simplifying assumptions created by a model to produce the target function more comfortable to learn.
Bias Variance Tradeoff
Low Bias - Suggests fewer algorithms about the form of the target function. For example, Decision Trees, k-Nearest Neighbors, and Support Vector Machines.
High Bias - Suggests more algorithms about the form of the target function. For example, Linear Regression, Linear Discriminant Analysis, and Logistic Regression.
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