A lot of things changed from OpenCV 2.4 to OpenCV 3.0. Among others, the machine learning module, which isn’t backward compatible. This is the OpenCV tutorial code for the SVM, update for OpenCV 3.0: #include <opencv2/core.hpp> #include <opencv2/imgproc.hpp> #include “opencv2/imgcodecs.hpp” #include <opencv2/highgui.hpp> #include <opencv2/ml.hpp> using namespace cv; using namespace cv::ml; int main(int, char**) { // … Read more
SVMs were originally designed for binary classification. They have then been extended to handle multi-class problems. The idea is to decompose the problem into many binary-class problems and then combine them to obtain the prediction. One approach called one-against-all, builds as many binary classifiers as there are classes, each trained to separate one class from … Read more
According to the official libsvm documentation (Section 7): LIBSVM implements the “one-against-one” approach for multi-class classification. If k is the number of classes, then k(k-1)/2 classifiers are constructed and each one trains data from two classes. In classification we use a voting strategy: each binary classification is considered to be a voting where votes can … Read more
Here’s a complete example, using the following functions from the Bioinformatics Toolbox: SVMTRAIN, SVMCLASSIFY, CLASSPERF, CROSSVALIND. load fisheriris %# load iris dataset groups = ismember(species,’setosa’); %# create a two-class problem %# number of cross-validation folds: %# If you have 50 samples, divide them into 10 groups of 5 samples each, %# then train with 9 … Read more
Scikit-learn uses LibSVM internally, and this in turn uses Platt scaling, as detailed in this note by the LibSVM authors, to calibrate the SVM to produce probabilities in addition to class predictions. Platt scaling requires first training the SVM as usual, then optimizing parameter vectors A and B such that P(y|X) = 1 / (1 … Read more
I’ve had to deal with this recently, and here’s what I ended up doing to get SVM to work for images. To train your SVM on a set of images, first you have to construct the training matrix for the SVM. This matrix is specified as follows: each row of the matrix corresponds to one … Read more