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Model Evaluation

Feature Selection

Feature Selection is a process of finding the best subset of attributes which better explain the relationship of independent (don’t train your model using correlated data via supervised learning since this reduces the accuracy) variables with target variables.

You can select the useful features based on various metrics such as domain knowledge or experience. We select feature(s) which may have higher impact on target variable.

Feature Selection Resources:

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