Logistic regression is a classification technique for classifying data points x (a vector) into one of K classes . It works by (essentially) projecting the datapoints onto a set of (pre-specified) features (which are simply vectors formed of functions of the datapoints’ components), and then finding linear separating (hyper-)planes in…

# Classification: Introduction

In this series of four (and eventually possibly more) blogs, I am going to look at classification methods, and in particular (at least in the first instance) I am going to look at neural network-type methods. This is a hot topic (again) at the moment, with the recent demonstration of…

# Intentionality Prediction

I’ve recently finished and submitted a paper on the interesting topic of intentionality prediction, that is, figuring out the intent of something from the action that it is taking. In the paper (one of a number that I have published in this area), we look at how we can infer…

# Hadoop Part IV: Online Parameter Estimation

For the final (for now) part of this series, I am going to extend the particle filter to do online parameter estimation using online Expectation-Maximization (EM) to calculate an estimate of the autoregression parameter at each stage of the particle filter. There are many options for online parameter estimation, including…

# Hadoop Part II: Particle Filters in Hadoop MapReduce

In this article, I’m going to go about implementing a basic particle filter in Hadoop MapReduce. This is really just a personal interest project for me to get started learning Hadoop based on an algorithm that I am familiar with and suits MapReduce (to some extent), but this might have…

# Hadoop Introduction: Using Hadoop for Sequential Monte Carlo (Particle Filter) Parameter Estimation

Recently, I have become interested in parameter estimation for sequential Monte Carlo (SMC) methods (primarily, but not exclusively, particle filters), due to writing about them for my forthcoming book (obligatory plug – sorry). And I’ve also become interested in learning about Hadoop (an interest not uncorrelated to my current job…

# A Brief Review of “Collaborative Filtering for Implicit Feedback Datasets” by Y. Hu, Y. Koren and C. Volinsky

During a recruitment process that I took part in, I was asked to write a review of the paper Collaborative Filtering for Implicit Feedback Datasets (2009) by Y. Hu, Y. Koren and C. Volinsky. In the review I gave a Bayesian interpretation of the model, which makes some of the parameters…