A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Improvement of the Fast Clustering Algorithm Improved by K-Means in the Big Data
2020
Applied Mathematics and Nonlinear Sciences
Clustering as a fundamental unsupervised learning is considered an important method of data analysis, and K-means is demonstrably the most popular clustering algorithm. In this paper, we consider clustering on feature space to solve the low efficiency caused in the Big Data clustering by K-means. Different from the traditional methods, the algorithm guaranteed the consistency of the clustering accuracy before and after descending dimension, accelerated K-means when the clustering centeres and
doi:10.2478/amns.2020.1.00001
fatcat:p4bw22zddbapfnx5nk2zfjhjuu