title: Python Scikit Random forest pred_proba outputs rounded off values
body: <p>I am using random forest in scikit learn for classification and for getting the class probabilities , I used pred_proba function. But it outputs probabilities rounded to first decimal place</p>
  
  <p>I tried with sample iris dataset</p>
  
  <pre><code>iris = load_iris()
  df = pd.DataFrame(iris.data, columns=iris.feature_names)
  df['is_train'] = np.random.uniform(0, 1, len(df)) &lt;= .75
  df['species'] = pd.Categorical(iris.target, iris.target_names)
  df.head()
  
  train, test = df[df['is_train']==True], df[df['is_train']==False]
  
  features = df.columns[:4]
  clf = RandomForestClassifier(n_jobs=2)
  y, _ = pd.factorize(train['species'])
  clf.fit(train[features], y)
  clf.predict_proba(train[features])
  </code></pre>
  
  <p>output probabilities</p>
  
  <pre><code>   [ 1. ,  0. ,  0. ],
     [ 1. ,  0. ,  0. ],
     [ 1. ,  0. ,  0. ],
     [ 1. ,  0. ,  0. ],
     [ 0. ,  1. ,  0. ],
     [ 0. ,  1. ,  0. ],
     [ 0. ,  1. ,  0. ],
     [ 0. ,  1. ,  0. ],
     [ 0. ,  1. ,  0. ],
     [ 0. ,  1. ,  0. ],
     [ 0. ,  0.8,  0.2],
     [ 0. ,  1. ,  0. ],
     [ 0. ,  1. ,  0. ],
     [ 0. ,  1. ,  0. ],
  </code></pre>
  
  <p>Is it the default output? Is it possible to increase the decimal places?</p>
  
  <p><strong>Note:</strong>
  Found the solution.
  Default no. of trees =10, after increasing no. of trees to hundred the precision  of probability is increased. </p>