A Research of Exploration on College Students' Organization Form Based on Clustering Algorithm

In this paper, K-means clustering algorithm is applied to the classification of college students, by which studies college students' organization form and then discovers new college students' organization from. By means of defining students' attributes, the whole text quantities and normalizes those attributes. After calculating weights and filtering those attributes, all data points are classified to K groups for the first time according to their intervals to initial centers which feature in the largest intervals to avoid K-means clustering algorithm's shortcomings. Using each group's average as new center, execute classification until stop standard is reached. Analyzing the classified groups by results of classification, common personal characters are easily to be figured out in each group. This research is considered to provide references and suggestions about college students' organization form newly discovered. How this classification results perform in the long run may need further study.