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Many Machine Learning articles and papers describe the wonders of the Support Vector Machine (SVM) algorithm. Nevertheless, when using it on real data trying to obtain a high accuracy classification, I stumbled upon several issues. I will try to describe the steps I took to make the algorithm work in practice. This model was implemented using R and the library "e1071". To install and use it type:. > install.packages("e1071"). > library("e1071"). When you want to classify data in two categories , few algorithms are better than SVM. It usually divides data in two different sets by finding a "line" that better separates the points. It is capable to classify data linearly (put a straight line to... Full story

4 days ago, 11 February