[This article was first published on Blend it like a Bayesian!, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

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Over the years I have learned quite a few things about machine learning but I have never thought of writing them down properly. Too often I can’t figure out exactly what I did when I look at my old codes. The time is NOW!

More importantly, I have fallen in love with the R programming language and the massive amount of useful packages from the R community. I want to talk about tricks, tools and useful resources for data mining with R (and sometimes my old favourite Matlab) here. 

One of the interesting tricks I learned is called “Bayesian Ensemble Learning”. It involves combining (i.e. blending) different models to improve overall prediction accuracy. Although it has its downside (e.g. computationally expensive, difficult to interpret …), it is certainly my favourite data mining technique at the moment. I also decided to name this blog with it long before I start writing this first post!

There is also a need to promote my own research project online. So I guess there will be times I talk about drainage design, green infrastructure and decision support systems. This is not the main focus of the blog but I will try to create some funky graphs and explain my research to a wider audience when the time is right (i.e. when I eventually master the art of graphics in R).

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