title: scikit-learn SVM with a lot of samples / mini batch possible?
body: <p>According to <a href="http://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html" rel="noreferrer">http://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html</a> I read: </p>
  
  <p>"The fit time complexity is more than quadratic with the number of samples which makes it hard to scale to dataset with more than a couple of 10000 samples."</p>
  
  <p>I have currently 350,000 samples and 4,500 classes and this number will grow further to 1-2 million samples and 10k + classes.</p>
  
  <p>My problem is that I am running out of memory. All is working as it should when I use just 200,000 samples with less than 1000 classes.</p>
  
  <p>Is there a way to build-in or use something like minibatches with SVM? I saw there exists MiniBatchKMeans but I dont think its for SVM?</p>
  
  <p>Any input welcome!</p>