Exploring unsupervised learning and dimensionality reduction algorithms

This post is aimed at exploring the ideas of unsupervised learning (clustering) and dimensionality reduction. The exploration is being done by experimenting with the following algorithms on two publicly available datasets — Principal Components Analysis Independent Components Analysis Random Projections Feature Selection using Information Gain k-Means Clustering Clustering using Gaussian Mixture Models The idea is… Continue reading Exploring unsupervised learning and dimensionality reduction algorithms