Author Archives: nivangio
Improving Adaboosting with decision stumps in R
Adaboosting is proven to be one of the most effective class prediction algorithms. It mainly consists of an ensemble simpler models (known as “weak learners”) that, although not very effective individually, are very performant combined. The process by which these … Continue reading
From JSON to Tables
“First things first”. Tautological, always true. However, sometimes some data scientists seem to ignore this: you can think of using the most sophisticated and trendy algorithm, come up with brilliant ideas, imagine the most creative visualizations but, if you do not know … Continue reading
Quick guide to parallel R with snow
Probably, the most common complains against R are related to its speed issues, especially when handling a high volume of information. This is, in principle, true, and relies partly on the fact that R does not run parallely…. unless you … Continue reading
Dashboards in R with Shiny and GoogleVis
Previously on this post, I introduced limitedly some features of the Shiny package. However, I felt the need of doing a new post related to Dashboards due to many reasons: a) Shiny has changed most of its functions and the … Continue reading
A new Sudoku Solver in R. Part 1
Sudoku is nowadays probably the most widespread puzzle game in the world. As such, it has an interesting variety of solving techniques, not just with paper and pencil but also with computers. Of course, I am not the first one … Continue reading
Social Media Monitoring tools in R with just a few lines
Social Media Analysis has become some kind of new obsession in Marketing. Every company wants to engage existing customers or attract new ones through this communication channel. Therefore, they hire designers, editors, community managers, etc. However, when it comes to … Continue reading
Animated graphs, another alternative for Data Visualization
The world of Data Visualization offers infinite variants to display our Data. However, there is still some reluctance in exploiting all the possibilities that computers give us nowadays in this field, probably not because of a rejection of novelties but … Continue reading
Working with geographical Data. Part 1: Simple National Infomaps
There is a popular expression in my country called “Gastar polvora en chimangos”, whose translation in English would be “spending gunpowder in chimangos”. Chimango is a kind of bird whose meat is useless for humans. So “spending gunpowder in chimangos” … Continue reading
Florence Nightingale and the importance of Data Visualization
Florence Nightingale is held as a heroine for the British people because of her work during the Crimean War. However, she would not have been so fairly recognised if she had not been also a superb statistician: in a brilliant … Continue reading