Aug 3, 2013 — Multidimensional Scaling (MDS) — Multidimensional scaling (MDS) is a way to reduce the dimensionality of data to visualize it.  We basically want to project our (likely highly dimensional) data into a lower dimensional space and preserve the distances between points.  The first time that... Read more

Jul 31, 2013 — Imputation of Missing Values — In a perfect world, my data is absolutely perfect, and I’ve collected every feature or metric for every person, to be fed cleanly into some model.  Now let’s recognize the obvious reality that having complete data is rarely the case.... Read more

Jul 29, 2013 — Self Organizing Maps (SOM) — The goal of the** Self Organizing Maps** (SOM) is to use unsupervised machine learning to represent complex data in a low (e.g, 2D) dimensional space.  They are actually types of artificial neural networks (ANNs), meaning that we are going to... Read more

Jul 29, 2013 — Vector Quantization — Vector Quantization is a method to compress data, and it’s considered a lossy technique because we are creating a new representation for a set of N observations that loses some of our information.  This happens because we represent each of... Read more