An Algorithm Framework for Drug-Induced Liver Injury Prediction Based on Genetic Algorithm and Ensemble Learning

. 2022 May 12;27(10):3112. doi: 10.3390/molecules27103112

Algorithm 1 Initialization

Input: $M$ : the amount of individuals in a population.
$K$ : the amount of feature subsets in an individual.
$S_{f s}$ : the size of feature index in a feature subset.
$S_{f}$ : feature size.
Output: $P_{0}$ : the first population of R-E-GA
1: for $m = 0 \dots \dots M$ do
2: $m = m + 1$
3: reset $f e a t u r e_s u b s e t$ to []
4: while $k = 0 \dots \dots K$ do
5: $k = k + 1$
6: add the $f e a t u r e_i n d e x$ randomly generated in $S_{f}$ range to $f e a t u r e_s u b s e t$
7: add $f e a t u r e_s u b s e t$ to $P_{0}$