Say we are doing classification analysis with classes labeled 0 through m-1. Let Ni be the number of observations in class i. There is much handwringing in the machine learning literature over situations in which there is a wide variation among the Ni. I will argue here, though, that the problem ... [Read more...]

The other day, I picked up the latest copy of the CAS’ journal, Variance and skipped to the back where Leigh Halliwell had an article. I hope that I’m well on record as being one of his biggest fans, but if not, let me remedy that now. Leigh Halliwell ... [Read more...]

ThinkToStart is growing and we need more people who help us on our mission to bridge the gap between data and business. Therefore we are looking for motivated R fans that help us to produce more great content. What is ThinkToStart? ThinkToStart started as a blog mainly about R tutorials ... [Read more...]

I’ll be giving a presentation on Thursday, 8 October on Panoptez, the interactive data analysis platform I’ve been developing. Panoptez …Continue reading → [Read more...]

Were you at the EARL London R Conference this year? See if you can find yourself in our selection of images of this popular event. Look good? Wish you were there? Still a chance to come to EARL Boston on … Continue reading → [Read more...]

by Bob Horton Microsoft Senior Data Scientist Learning curves are an elaboration of the idea of validating a model on a test set, and have been widely popularized by Andrew Ng’s Machine Learning course on Coursera. Here I present a simple simulation that illustrates this idea. Imagine you use ... [Read more...]

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A function for testing auto.arima() This is the third, and the last from me on this particular topic for a while, in a series of posts on fitting time series models and comparing time series to eachother, originally inspired by a question on the Cross-Validated Q&A site. In ... [Read more...]

By Lewis Rendell, R Consultant Intern, Mango Solutions As a mathematics and statistics student, R has been invaluable during my studies. With the number of packages available for data analysis and the ease with which simple and complex functions can … Continue reading → [Read more...]

  Competition Time! Mango Solutions are pleased to offer you an opportunity to win a FREE two day Conference Pass  to the EARL (Effective Application of the R Language) Conference in Boston on 3-4 November. Conference Reception at Boston Science Museum on Tuesday … Continue reading → [Read more...]

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We released version 0.2.2 of ChainLadder a few weeks ago. This version adds back the functionality to estimate the index parameter for the compound Poisson model in glmReserve using the cplm package by Wayne Zhang. Ok, what does this all mean? I will r... [Read more...]

We released version 0.2.2 of ChainLadder a few weeks ago. This version adds back the functionality to estimate the index parameter for the compound Poisson model in glmReserve using the cplm package by Wayne Zhang. Ok, what does this all mean? I will run through a couple of examples and look ... [Read more...]

Using R Functions in Python [Read more...]

Geomorph users,We have uploaded version 2.1.7 of geomorph to CRAN. The windows binaries have been compiled and the tarball is available. However, subsequent to this, we found that under certain input scenarios, some of the changes we made to underlying support code had undesirable outcomes. We have corrected these issues ... [Read more...]

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If you've developed a useful function in R (say, a function to make a forecast or prediction from a statistical model), you may want to call that function from an application other than R. For example, you might want to display the forecast (calculated in R) as part of a ... [Read more...]

Recently I wrote a post for DataScience+ (which by the way is a great website for learning about R) explaining how to fit a neural network in R using the neuralnet package, however I glossed over the “how to choose the number of neurons in the hidden layer” part. The ... [Read more...]