SVM^light is an implementation of the Support Vector Machine providing methods for efficient estimation methods for both error rate and precision/recall. SVM^light exploits that the results of most leave-one-outs (often more than 99%) are predetermined and need not be computed. Further more it can also train SVMs with cost models. Many tasks have the property of sparse instance vectors. This implementation makes use of this property which leads to a very compact and efficient representation. Continue reading “Install SVM-light for R” →