Data clustering, or cluster analysis, is the process of grouping data items so that similar items belong to the same group/cluster. There are many clustering techniques. In this article I'll explain ...

This is the repository for the Python version of the ssg_pymeans package. The R version is available here. This package implements the classical unsupervised clustering method, k-means for ...

K-means is a commonly used algorithm in machine learning. It is an unsupervised learning algorithm. It is regularly used for data clustering. Only the number of clusters are needed to be specified for ...

Listing 1: Clustering with K-Means Program Structure # k_means.py # Anaconda 4.1.1 import numpy as np def mm_normalize(data): . . . def ... While this article focuses on using Python, I've also ...

In centroid-based clustering, clusters are represented by a centroid. It is an iterative algorithm in which the notion of similarity is derived by how close a data point is to the centroid of the ...