Selection for Machine Learning

 Python-based Automated Feature Selection for Machine Learning

The process of choosing the most significant and instructive features from a dataset is known as feature selection. It is one of the most crucial processes in the machine learning modeling pipeline since it has a big impact on the effectiveness and predictive capacity of the model.

Due to the short deadlines in real-life projects and the underestimating of its performance effects, feature selection is sometimes neglected during the creation of machine learning models, despite the fact that it has several advantages. There are several feature selection methodologies, and skipping this important stage may result from not understanding which one(s) to utilize.

Using the beneficial effects of feature selection on machine learning models as a viable solution to time-related problems is

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