title: Time series forecasting with scikit learn
body: <p>I am a complete newbie to SVM-based forecasting and so looking for some guidance here. I am trying to set-up a python code for forecasting a time-series, using SVM libraries of scikit-learn. </p>
  
  <p>My data contains X values at 30 minute interval for the last 24 hours, and I need to predict y for the next timestamp. Here's what I have set up - </p>
  
  <pre><code>SVR(kernel='linear', C=1e3).fit(X, y).predict(X)
  </code></pre>
  
  <p>But for this prediction to work, I need the X value for the next timestamp, which is not available. How do I set this up to predict future y values?</p>