The Analysis of Non-Significant Feature Data Mining in Big Data Environments

摘要

In order to cope with the problem of low precision in data mining, it is necessary to study the non-significant features of data mining methods. The current method shows efficiency bias in the data mining. In this paper, a non-significant feature data mining method based on Ant Colony Clustering is proposed. This method extracts the characteristics of data clustering which manifest the significant characteristics of data mining in a big data environment. Experiments show that this method is more accurate when data mining.