Photovoltaic fault arc feature selection method combining filtering type evaluation strategy and packaging type evaluation strategy

The invention discloses a photovoltaic fault arc feature selection method combining a filtering type evaluation strategy and a packaging type evaluation strategy, and the method comprises the steps: carrying out the processing of a to-be-selected multi-feature set through employing a ReliefF algorithm, endowing different features with corresponding weights based on fault arc feature correlation, screening out the features with lower weights, and if the number of needed features is given, obtaining a required optimal feature set by adopting a maximum correlation and minimum redundancy algorithm, otherwise, obtaining a series of non-redundant feature sets by adopting the maximum correlation and minimum redundancy algorithm, and performing solving by adopting multi-objective optimization of classifier accuracy and the number of features to obtain the optimal feature set. The optimal data set meeting different requirements is constructed by combining multiple feature selection methods, the optimal features used f