1
vote
2answers
28 views

SVM for unbalanced data

I want to attempt to use Support Vector Machines (SVMs) on my dataset. Before I attempt the problem though, I was warned that SVMs dont perform well on extremely unbalanced data. In my case, I can ...
0
votes
0answers
33 views

Sample size for binary text classification

In my application as a Binary text classification, one class has around 36,000 sample and another one has around 300 samples. I under-sample the first class. So, each class will have ~ 300 samples. ...
2
votes
2answers
2k views

LibSVM cost weights for unbalanced data doesn't work

I have a dataset where the number of negative labeled values is 163 times the number of positive labeled values. That is, I have an unbalanced data set. I tried: ...
6
votes
1answer
576 views

A priori selection of SVM class weights

I remember seeing/reading somewhere that for multiclass SVMs with unbalanced data, there was a way to determine the class weights from the training data (rather than X validation). Does anyone know ...
3
votes
3answers
1k views

SVM vs. artificial neural network

I have multiclass unbalanced data (4 class with 15% 25% 45% 15% data in each class). Which method is good for classification of such data- SVM or ANN? UPDATE- Let me make the question little more ...
1
vote
1answer
2k views

Best way to handle unbalanced multiclass dataset with SVM

I'm trying to build a prediction model with SVMs on fairly unbalanced data. My labels/output have three classes, positive, neutral and negative. I would say the positive example makes about 10 - 20% ...