As a result, in machine learning, when models are more flexible they can easily fit the noise in the data as well and consequently leading to over-fitting.
This is analogous to Logistic Regression and Decision Tree.
Decision Tree being more flexible than Logistic Regression is prone to over-fitting the data.
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