Introduction to Model-Based Clustering There’s another way to deal with clustering problems: a model-based approach, which consists in using certain models for clusters and attempting to optimize…
View More Clustering as a Mixture of GaussiansCategory: Statistics
Hierarchical Clustering Algorithms
How They Work Given a set of N items to be clustered, and an N*N distance (or similarity) matrix, the basic process of hierarchical clustering…
View More Hierarchical Clustering AlgorithmsK-Means Clustering
The Algorithm K-means (MacQueen, 1967) is one of the simplest unsupervised learning algorithms that solve the well known clustering problem. The procedure follows a simple…
View More K-Means ClusteringClustering: An Introduction
What is Clustering? Clustering can be considered the most important unsupervised learning problem; so, as every other problem of this kind, it deals with finding a structure in a…
View More Clustering: An IntroductionHow to choose between Pearson and Spearman correlation?
How do I know when to choose between Spearman’s ρ and Pearson’s r? My variable includes satisfaction and the scores were interpreted using the sum of the scores.…
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