[Retracted] An Information Entropy Embedding Feature Selection Based on Genetic Algorithm

Algorithm 1

Information entropy weight distribution.

	Input: NumPy independent variable dataset
	Output: Weight list
(1)	Normalize based on custom functions
(2)	Export data shape, the number of rows is , the number of columns is
(3)	Calculate the Proportion
(4)	Figure out the entropy
(5)	Calculate the weight of each indicator
(6)	Form weight list