GitHub / pradeepdev-1995 / Feature-Selection-Techniques

Feature selection techniques in machine learning is a process of automatically or manually selecting the subset of most appropriate and relevant features to be used in model building. Here we are taking a machine learning regression problem and shows the different steps in feature selection process

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Topics: bivariate-analysis, correlation, feature-engineering, feature-extraction, feature-selection, filter-based-feature-selection, linear-regression, machine-learning, machine-learning-algorithms, mlextend, outlier-detection, seaborn, sequential-feature-selection, univariate-analysis, visualization, wrapper-based-selection

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