title: How can we calculate accuracy for the Random forest classifier if we are using 4 label classification?
body: <p>I am trying to predict the quality attributes of the product which have been sold over last decade.
  Based on the likes/dislikes i have kept the 4 label for the product
  Labels are: bad , good, very good,very bad</p>
  
  <p>I have downloaded the last decade data and categorized the samples in these 4 labels. When i put the input in random forest classifier , it is giving the valid result and giving the feature importance:</p>
  
  <p>Here is the code for same:</p>
  
  <pre><code>classifier = RandomForestClassifier(
          n_estimators=100, n_jobs=6, oob_score=True, random_state=50,
          max_features="auto", min_samples_leaf=50
      )
      '''
  
      classifier = RandomForestClassifier(
          n_estimators=100, n_jobs=6, oob_score=True, random_state=50#, max_depth=3
      )
  </code></pre>
  
  <p>I just want to understand , how we can calculate the accuracy of the model as it has 4 labels.</p>