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The Clusters-Features package allows data science users to compute high-level linear algebra operations on any type of data set. It computes approximatively 40 internal evaluation scores such as Davies-Bouldin Index, C Index, Dunn and its Generalized Indexes and many more ! Other features are also available to evaluate the clustering quality.
Python toolbox intended for GIS Archaeology tools developed by Matthew Bova
This repository contains clustering techniques applied to minute weather data. It contains K-Means, Heirarchical Agglomerative clustering. I have applied various feature scaling techniques and explored the best one for our dataset
Clustering usuarios de cartão de crédito usando KMeans.
Unsupervised learning algorithms to cluster students of a public school
Clustering algorithms to segment clients of a distribution company
Algorithms for computing cluster validity indices including a new correlation-based called Wiroonsri index