14 Mar 2016
This blog post is about randomly searching for the optimal parameters of various algorithms employing resampling in R. A randomized search simply samples parameter settings a fixed number of times from a specified subset of the hyperparameter space of a learning algorithm. This method has been found to be more effective in high-dimensional spaces than an exhaustive search (grid-search). Moreover, the purpose of random search is to optimize the performance of an algorithm using a resampling method such as cross-validation, bootstrapping etc. for a better generalization.
14 Feb 2016
This blog post is about feature selection in R, but first a few words about R. R is a free programming language with a wide variety of statistical and graphical techniques. It was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team. R comes by installation with a core number of packages, which can be extended with more than 7,801 additional packages (as of January 2016). Packages can be downloaded from either the Comprehensive R Archive Network (CRAN) or from other sources like Github or the Bioconductor. Many of those statistical packages are written in R itself, however, a nice feature of R is that it can be linked to lower-level programming languages ( such as C or C++ ) for computationally intensive tasks. More information about R can be found here.
31 Jan 2016
In my first blog post, I’ll explain how I created my blog. I don’t have any knowledge of building web sites and somehow I thought it will be difficult. However, after lots of ‘googling’, I finally managed it.
I use the Lanyon theme of the Poole sliding sidebar theme, which is a jekyll setup. For all those, like me, who a week ago didn’t know what Poole or jekyll is, the following two links can give some more details,