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What is K-Means Clustering Explained about?

The document discusses ensemble techniques and unsupervised learning in machine learning, focusing on the K-Means algorithm and the k-Nearest Neighbors (k-NN) method. It outlines the steps involved in the K-Means clustering process, its advantages and weaknesses, as well as the workings of the k-NN algorithm for classification tasks. Additionally, the document introduces the Expectation-Maximization (EM) algorithm for parameter estimation in probabilistic models with latent variables.

Author

shrijith23

Language

EN