Continuing with his standard pace of approximately one new version per month, Conrad released a new minor release of Armadillo a few days ago. As before, I had created a GitHub-only pre-release which was tested against all eighty-seven (!!) CRAN dependents of our RcppArmadillo package and then uploaded RcppArmadillo 0.4.450.0 to CRAN. ... [Read more...]

I was inspired by this blog post and thought I could do the same thing in R.  Well I posted the code in Google+Here are my results.  Not bad. [Read more...]

I recently attended a week-long R course in Newcastle, taught by Colin Gillespie. It went from “An Introduction to R” to “Advanced Graphics” via a day each on modelling, efficiency and programming. Suffice to say it was an intense 5 days! Overall it was the best R course I’ve been ... [Read more...]

[This article is adapted and expanded from presentations at Nvidia's GTC conference in March, as well as UseR! in July, 2014.] The Random Forest algorithm is a well-known tool for data analysis. It yields robust predictive models for vastly different data sets, serving as a sort of Swiss Army Knife in ... [Read more...]

In this tutorial I am going to describe a straightforward way of how to make use of Twitter’s REST API v1.1. For that purpose I composed a little package (RTwitterAPI), so that requesting data just needs the API URL, the API parameters … Continue reading → [Read more...]

You're probably familiar with the classic Travelling Salesman problem: given (say) 20 cities, what is shortest route you can take that passes through all 20 cities and returns to the starting point? It's a difficult problem to solve, because you need to try all possible routes to find the minimum, and there ... [Read more...]

Following up on my previous posts about H2O Deep Learning (TTTAR1) and RUGSMAPS (TTTAR2), here is a quick update on two interesting things I have been working on: a Kaggle tutorial and a new RUGSMAPS app.Short Tutorials based on a Kaggle CompetitionFirst of all, I would like to ... [Read more...]

First things first, Dirk Eddelbuettel was recently named ordinary. This seems contradictory, since Dirk is a... [Read more...]

[This article was first published on Rmetrics blogs, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your [Read more...]

Supposedly, projective tests (e.g., the inkblots of psychoanalysis) contain sufficient ambiguity that "what you see" reveals some aspect of your thinking that has escaped your awareness. Although the following will provide no insight into your neurotic... [Read more...]

I’m giving a talk this Friday (September 26, from 6 – 8 PM) on my current research into interest detection on Twitter. The talk …Continue reading → [Read more...]

My last experience with Linux was back in 2002/2003. At that time pretty much everything on Linux was done in the console. I remmember struggling for days with a simple Wifi connection because drivers were not readily available. Things have changed dramatically since then. Last week I installed Linux (Ubuntu 14.04)  on ... [Read more...]

Sometimes, several strands of thought come together in one place. For me right now, it’s the Wikipedia page “Ebola virus epidemic in West Africa”, which got me thinking about the perennial topic of “data wrangling”, how best to provide public data and why I can’t shake my irritation ... [Read more...]

On a scale of one to straight up voodoo, Hidden Markov Models (HMMs) are definitely up there for me.They have all sorts of applications, and as the name suggests, they can be very useful when you wish to use a Markovian approach to represent some stochastic process.In loose ... [Read more...]

Twelve days after the initial commit, pipeR tutorial is released! If you want to write R code fluently and process data elegantly, I strongly recommend that you read this tutorial which is designed to serve as a complete guide to pipeR package, inclu... [Read more...]

Welcome to last part of the series post again! In previous part I discussed about the solutions to the questions mentioned in first part. In this part, we will implement whole scenario using R and MySQL together and see how we can process bigdata(computationally ) Let us recall those questions ... [Read more...]

This summer, for the first time, I took three Dauphine undergraduate students into research projects thinking they had had enough R training (with me!) and several stats classes to undertake such projects. In all cases, the concept was pre-defined and “all they had to do” was running a massive flow ... [Read more...]

Welcome to the second part of the series blog posts. In first part we tried to understand the challenges of fitting predictive model to the large dataset. In this post I will discuss about the solution approach to that challenges. Let’s start rolling. As machine learning technique requires accessing ... [Read more...]

Here is a short post on how to generate a quick slope field in R and Python. If you do not know what a slope field is, well I am not the best person to explain it to you since it is a relative new concept for me as well. ... [Read more...]

Wellcome to the series blog posts. Since long time, I am writing post on Machine learning with R. Today I am gonna discuss on big data problem while fitting machine learning on it and its solution using MySQL and R. Before we jump directly to solution, let us discuss about ... [Read more...]