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Support Vector Machine refers to "a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis."

1 vote
2 answers
826 views

Moving from support vector machine to neural network (Back propagation)

Currently, in SVM, I have 200 features (divided into 4 main categories), which is used to recognize the text. … In SVM, I have two class classification (basically, true and false) and multi-class classification (labels), how this difference will apply to the output layer of the neural networks? …
TLD's user avatar
  • 133
0 votes
2 answers
2k views

Multi class classification always have better result than one class classification?

Currently I'm using svm to classify the test samples to two different classes (True and False). … Then, Did I misunderstand something about one class classification with svm ? Thank you very much. …
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  • 133
1 vote
3 answers
3k views

Supervised or unsupervised learning problem

I have been using supervised learning (neural network and svm with one class classification) but I think I'm doing it in a wrong way. … With svm one classification: Currently I'm using libsvm library and got accuracy at 0%, I don't know should this be problem from training data or not... …
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  • 133
0 votes
1 answer
4k views

One class classification with libsvm. Accuracy results in 0%

used y as data value): 1 1:y 2:y "until" 200:y For data preparation (training and testing set), I set upper and lower scaling limit to +-1 -l -1 -u 1 For training, I use svm_type is one class svm
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  • 133