title: shortening runtime for sklearn Logistic Regression
body: <p>I currently have a Flask server that takes in data and applies a Logistic Regression algo to it. However, I plan on turning it into a AWS Lambda function and I would like the algo to be as efficient as possible time wise.</p>
  <p>The input is something like this:</p>
  <p><a href="https://i.stack.imgur.com/JmVi3.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/JmVi3.png" alt="Input" /></a></p>
  <p>The algo part of the code is a few lines:</p>
  <pre><code>from sklearn.linear_model import LogisticRegression
  classifier = LogisticRegression(random_state = 0)
  classifier.fit(X_train, y_train)
  y_predict_test = classifier.predict(X)
  oldlist = classifier.predict_proba(X)
  problist = sortProb(oldlist)
  return(problist)
  </code></pre>
  <p>This currently takes about 2.6 seconds to process. Is there anyway to speed it up?</p>
  <p>Thanks</p>