NEWS.md
In clustlearn: Learn Clustering Techniques Through Examples and Code

clustlearn 1.0.0

New features

New kmeans() function to perform K-Means clustering on a set observations and (if selected) see the step-by-step clustering procedure;
New dbscan() function to perform DBSCAN clustering on a set observations and (if selected) see the step-by-step clustering procedure;
New gaussian_mixture() function to perform Gaussian Mixture Model with Expectation Maximization clustering on a set observations and (if selected) see the step-by-step clustering procedure;
New agglomerative_clustering() function to perform Agglomerative Hierarchical Clustering clustering on a set observations and (if selected) see the step-by-step clustering procedure;
New divisive_clustering() function to perform Divisive Hierarchical Clustering (Bisecting K-Means) clustering on a set observations and (if selected) see the step-by-step clustering procedure;
New db1 data.frame with 500 observations (2 features) in the shape of two concentric circumferences;
New db2 data.frame with 500 observations (2 features) in the shape of two rotated moons;
New db3 data.frame with 500 observations (2 features) in the shape of three Gaussian distributions with varying parameters;
New db4 data.frame with 500 observations (2 features) in the shape of three elongated clusters;
New db5 data.frame with 500 observations (2 features) in the shape of three isotropic clusters;
New db6 data.frame with 500 observations (2 features) randomly distributed across the bi-dimensional plane.