A new distance measurement and its application in K-Means Algorithm
组织者
演讲者
石想
时间
2023年01月11日 21:30 至 22:00
地点
Online
摘要
K-Means clustering algorithm based on Euclidean distance only pays attention to the linear distance between samples, but ignores the overall distribution structure of the dataset (i.e. the fluid structure of dataset). A new distance measurement, namely, view-distance, is applied to the K-Means algorithm. On the classical manifold learning datasets, S-curve and Swiss roll datasets, not only this new distance can cluster the data according to the structure of the data itself, but also the boundaries between categories are neat dividing lines.