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

Algorithm 2

Selection in GA.

	Input: Population , fitness list
	Output: New population
(1)	Normalize pop and construct penalty map for as
(2)	Calculate the fitness sum and cumulative probability
(3)	Create cumulative probability list
(4)	For i in range(len()) do
(5)	Generate 0-1 random numbers into two lists
	End for
(6)	Sort
(7)	Traverse the list without exceeding the scope of the list and . If the value of this position of is less than the value of the current position of , the genotype at the current position in is stored in the temporary gene register . Position number in  + 1, otherwise the current position +1, until finish traversing.
(8)	Perform step 7 on and so that is formed.
(9)	Compare the value of each position of and , select the greater value and put it into