title: How can i train multiple times an SVM classifier from sklearn in Python?
body: <p>I was wandering if it possible to train the SVM classifier from sklearn in Python many times inside a for loop. I have in mind something like the following:</p>
  
  <pre><code>for i in range(0,10):
      data = np.load(somedata)
      labels = np.load(somelabels)
      C = SVC()
      C.fit(data, labels)
      joblib.dump(C, 'somefolderpath/Model.pkl')
  </code></pre>
  
  <p>I want my model to be trained for each one of the 10 data and their labels. Is that possible in that way or do i have to append all the data and labels into two corresponding arrays containing the whole data and labels from my 10 items?</p>
  
  <p><strong>EDITED</strong>: If i want to train a separate classifier for each subject. Then how would the above syntax look like? Is my edit correct?
  And when i want to load the specific trained classifier for my specific subject, can i do:</p>
  
  <pre><code>C = joblib.load('somefolderpath/Model.pkl')
  idx = C.predict(data)
  </code></pre>
  
  <p>?</p>