Support vector machines (SVMs) are a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis.
I currently have two numpy arrays: X - (157, 128) - 157 sets of 128 features Y - (157) - classifications of the feature sets …
python tensorflow machine-learning svmI have been trying to grasp the basics of Support Vector Machines, and downloaded and read many online articles. But …
algorithm machine-learning svm libsvmI am currently studing svm and was wondering what the application of svm`s with linear kernel is. In my …
machine-learning classification svm mathematical-optimizationI'm using the current stable version 0.13 of scikit-learn. I'm applying a linear support vector classifier to some data using the …
python scikit-learn classification svm normalizationI want to find out the error rate using svm classifier in python, the approach that I am taking to …
python machine-learning svm scikits scikit-learnI am looking for a library that, ideally, has the following features: implements hierarchical clustering of multidimensional data (ideally on …
cluster-analysis machine-learning svmI am currently working on a projet to perform image recognition. There is a big set of images and I …
python image-processing classification svm image-recognitionHow can find what the vector w is, i.e. the perpendicular to the separation plane?
matlab svm libsvmI'm currently working on classifying images with different image-descriptors. Since they have their own metrics, I am using precomputed kernels. …
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