The sklearn.cluster.KMeans module in Python is a part of the scikit-learn library which provides a way to perform K-means clustering. K-means clustering is an unsupervised learning algorithm used for grouping similar data points into clusters. The KMeans module allows you to specify the number of clusters to create and the algorithm will iteratively assign data points to clusters and optimize the positions of the centroid of each cluster. It offers various methods to fit the model, predict the clusters for other data points, and evaluate the quality of the clustering. It is a widely used module for clustering analysis in machine learning and data analysis tasks.
Python KMeans - 60 examples found. These are the top rated real world Python examples of sklearn.cluster.KMeans extracted from open source projects. You can rate examples to help us improve the quality of examples.