Comparing R to Matlab for Data Mining

Question

Instead of starting to code in Matlab, I recently started learning R, mainly because it is open-source. I am currently working in data mining and machine learning field. I found many machine learning algorithms implemented in R, and I am still exploring different packages implemented in R.

I have a quick question: how do you compare R to Matlab for data mining application, its popularity, pros and cons, industry and academic acceptance, etc.? Which one would you choose and why?

I went through various comparisons for Matlab vs R against various metrics but I am specifically interested to get an answer for its applicability in Data Mining and ML. Since both languages is pretty new for me I was just wondering if R would be a good choice or not.

I appreciate any kind of suggestions.

Answer 1

MATLAB and R have different libraries and code syntax, but the same functionalities.

 

The Neural Network Toolbox, the Optimization Toolbox, Statistics Toolbox, and Curve Fitting Toolbox are each highly desirable for someone using MATLAB for ML/Data Mining work, but they are all separate from the base MATLAB environment--in other words, they have to be purchased separately.

MATLAB is commercial and commonly used for mathematical processing. MATLAB is pretty slower than R and Python.

R is used for statistical analysis and data processing on a small scale. It has a very vast collection of packages, that are used to do almost anything you might imagine with data and they are easy to install. As a general programming language, it is much slower than Python and the syntax is quite confusing. 

To learn more about R, you can check out this informative tutorial blog, which helps you gain the basic insights of this vast language.