Abstract: The present disclosure relates to a machine learning method and apparatus using steps feature selection based on a genetic algorithm, and the machine learning method includes defining a feature set including a plurality of features, generating a plurality of feature combinations including n-dimensional features (n is a natural number) for the feature set, independently constructing feature models for the plurality of feature combinations and calculating prediction accuracy for each of the feature models as a prediction result for a predetermined data set, arranging the feature models according to the prediction accuracy to determine at least one good feature model that satisfies a preset criterion, determining at least one good feature from among features included in a corresponding feature set of the at least one good feature model, and updating the feature set to include only the at least one good feature and re-determining a good feature model for a (n+1)-dimensional feature combination based on the update