Novel Automatic Filter-Class Feature Selection for Machine Learning Regression

With the increased focus on application of Big Data in all sectors of society, the performance of machine learning becomes essential. Efficient machine learning depends on efficient feature selection algorithms. Filter feature selection algorithms are model-free and therefore very fast, but require a threshold to function. We have created a novel meta-filter automatic feature selection, Ranked Distinct Elitism Selection Filter (RDESF) which is fully automatic and is composed of five common filters and a distinct selection process.

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