Using googleVis via R provides lots of options to create nice google visualizations. I was trying to create some charts while exploring the Annual Nominal Fish Catches Data on Kaggle. I wanted to create a line motion chart and exclude the default bubble chart. So I played with the options ... [Read more...]

Clustering allows us to better understand how a sample might be comprised of distinct subgroups given a set of variables. While many introductions to cluster analysis typically review a simple application using continuous variables, clustering data of mixed types (e.g., continuous, ordinal, and nominal) is often of interest. The ... [Read more...]

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Text mining is a new challenge for machine wandering practitioners. The increased interest in the text mining is caused by an augmentation of internet users and by rapid growth of the internet data which is said that in 80% is a text data. Extracting information from articles, news, posts and comments ... [Read more...]

We are delighted to announce the full agenda and impressive line up of speakers for September’s EARL Conference. EARL 2016 will feature the largest number of talks yet with 3 streams and 48 presentations. We have a fantastic range of cross-industry representation … Continue reading → [Read more...]

by Lourdes O. Montenegro Lourdes O. Montenegro is a PhD candidate at the Lee Kuan Yew School of Public Policy, National University of Singapore. Her research interests cover the intersection of applied data science, technology, economics and public policy. Many of us now find it hard to live without a ... [Read more...]

In part 1, we went over how to use data visualization and data analysis prior to machine learning. For example, we discussed how to visualize the data to identify potential issues in the dataset, examine the variable distributions, etc. In this blog post, we’ll continue by building a very simple ... [Read more...]

[This is a guest post by Ned Bicare, PhD]   Start the p-hacker app! My dear fellow scientists! “If you torture the data long enough, it will confess.” This aphorism, attributed to Ronald Coase, sometimes has been used in a disrespective manner, as if it was wrong to do creative data ... [Read more...]

Welcome to Introduction to R for Data Science, Session 8: Intro to Text Mining in R, ML Estimation + Binomial Logistic Regression [Web-scraping with tm.plugin.webmining. The tm package corpora structures: assessing document metadata and content. Typical corpus transformations and Term-Document Matrix production. A simple binomial regression model with tf-idf scores ... [Read more...]

Today I am happy to announce a new Facebook group: R, Maps and Open Data. If you like this blog, then you should join this group! It’s free to join. This is my first time creating a Facebook group, and I am viewing it as both an experiment and ... [Read more...]

R is useful for many things. But, it is not only useful! There is plenty of fun to be had as well. In celebration of Summer I'm going to take a look at some useless (but fun!) R packages. Fortune teller fortunes is probably the best-known "just... [Read more...]

Appendix to Session 8: Intro to Text Mining in R, ML Estimation + Binomial Logistic RegressionWelcome to Introduction to R for Data Science, Session 8: Intro to Text Mining in R, ML Estimation + Binomial Logistic Regression [Web-scraping with tm.plugin.webmining. The tm package corpora structures: assessing document metadata and content. Typical corpus ... [Read more...]

I’m happy to say that the represtools package is now on CRAN. I’m so giddy that I’m writing this post not that long after it was accepted. This means that binaries haven’t been built yet and it may not have been propagated to all of the ... [Read more...]

tryCatch is one of the functions that allows the users to handle errors in a simple way. With it, you can do things like: if(error), then(do this). Take the following example:

sqrt("a")
Error in sqrt("a") : non-numeric argument to mathematical function

Now maybe you’d want something to happen when such an error happens. You can achieve ... [Read more...]

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In our previous post, we covered {mscsweblm4r}, a R package available on CRAN that wraps the Microsoft Cognitive Services Web Language Model REST API. In today's post, we'll go over {mscstexta4r}, a new R package that gives us access to another silo of Microsoft's NLP technology, its Text ... [Read more...]

In our previous post, we covered {mscsweblm4r}, a R package available on CRAN that wraps the Microsoft Cognitive Services Web Language Model REST API. In today's post, we'll go over {mscstexta4r}, a new R package that gives us access to another silo of... [Read more...]

The forecast package for R, created and maintained by Professor Rob Hyndman of Monash University, is one of the more useful R packages available available on CRAN. Statistical forecasting — the process of predicting the future value of a time series — is used in just about every realm of data analysis, ... [Read more...]