The Research of Imbalanced Data Set of Sample Sampling Method Based on K-Means Cluster and Genetic Algorithm

The classification favors seriously to the most kinds when we use the traditional sorter to classify the imbalanced data set. In order to effectively enhance classified performance of the minority kind in the imbalanced data set, we proposed one kind minority kind of sample sampling method based on the K-means cluster and the genetic algorithm in view of this question. We used K-means algorithm to cluster and group the minority kind of sample, and in each cluster we use the genetic algorithm to gain the new sample and to carry on the valid confirmation. Finally, through using KNN and SVM sorter we proved the method validity in the simulation experiment.