I am trying to use SVM Light to learn a classifier for the OpenCV2.2 HOG Descriptor. I get a float vector output from the HOG descriptor.
I have simple xor problem that I want to learn using the RBF kernel in libsvm.When I train the java libsvm using an XOR problem like:
Some questions of using the opencv CvSVM What kind of svm is it using? Is it using svmligh开发者_如何转开发t? OpenCV2.2 has svmlight, but I cannot find much references to it.
What is the proper way to normalize feature vectors for use in a linear-kernel SVM? Looking at LIBSVM, it looks like it\'s done by just rescaling each feature to a single standard upper/lower range.H
I\'m implementing a nonlinear开发者_高级运维 SVM and I want to test my implementation on a simple not linearly separable data. Google didn\'t help me find what I want. Can you please advise me where I
I have a standard {-1,+1} machine learning problem. The main difference is that the data points are binary 开发者_如何学JAVAstrings, so their prooximity is measured by Hamming distance.
I am using libsvm to train a SVM with hog features. The model file has n support vectors. But when I try to use it in OpenCV\'s SVM I found that there is o开发者_运维技巧nly one vector in OpenCV\'s mo
I am new to machine learning. I am familiar with 开发者_如何学编程SVM , Neural networks and GA. I\'d like to know the best technique to learn for classifying pictures and audio. SVM does a decent job
I\'m using regression SVMs in python and I am wondering if there is any way to get a \"confidence-measure\" value for its predictions.
I\'m having problems getting PCA and Eigenfaces working using the latest C++ syntax with the Mat and PCA classes. The older C syntax took an array of IplImage* as a parameter to perform its processing
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