John Ramey Statistics and Machine Learning

A Brief Look at Mixture Discriminant Analysis

Lately, I have been working with finite mixture models for my postdoctoral work on data-driven automated gating. Given that I had barely scratched the surface with mixture models in the classroom, I am becoming increasingly comfortable with them. With this in mind, I wanted to explore their application to classification because there are times when a single class is clearly made up of multiple subclasses that are not necessarily adjacent.

High-Dimensional Microarray Data Sets in R for Machine Learning

Much of my research in machine learning is aimed at small-sample, high-dimensional bioinformatics data sets. For instance, here is a paper of mine on the topic.

How to Download Kaggle Data with Python and requests.py

Recently I started playing with Kaggle. I quickly became frustrated that in order to download their data I had to use their website. I prefer instead the option to download the data programmatically. After some Googling, the best recommendation I found was to use lynx. My friend Anthony recommended that alternatively I should write a Python script.

Setting Up the Development Version of R

My coworkers at Fred Hutchinson regularly use the development version of R (i.e., R-devel) and have urged me to do the same. This post details how I have set up the development version of R on our Linux server, which I use remotely because it is much faster than my Mac.

Chapter 2 Solutions - Statistical Methods in Bioinformatics

As I have mentioned previously, I have begun reading Statistical Methods in Bioinformatics by Ewens and Grant and working selected problems for each chapter. In this post, I will give my solution to two problems. The first problem is pretty straightforward.