The feature extraction is a kind of dimensionality reduction technique to reduce the number of features in the dataset, to avoid overfitting risk, speed up the training, improve the accuracy, enhanced data visualization, and much more benefits. This is done by generating new features from the existing ones while discarding the original features. So, in layman’s language, it is the process of reducing the number of features of the dataset, to only what is necessary for the algorithm to process accurate outputs.
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