title: ValueError: bad input shape (37533, 3) Gradient Boosting Error in fit() method
body: <p>I am using Machine Learning Classification techniques Random Forest &amp; Gradient Boosting:</p>
  
  <p>Below is the code for Random Forest which works fine:</p>
  
  <pre><code>from sklearn.ensemble import RandomForestClassifier
  model = RandomForestClassifier(n_estimators=100, min_samples_leaf=10,     
  random_state=1)
  model.fit(x_train, y_train)
  print(model.score)
  #Accuracy of prediction
  y_pred = model.predict(x_test)
  #Mean Standard Error
  mean_squared_error(y_pred, y_test)
  model.score(x_test, y_test)
  Out[423]: 0.80038542832276516
  </code></pre>
  
  <p>Now the second classifier Gradient Boosting which gives an error:</p>
  
  <pre><code>from sklearn.ensemble import GradientBoostingClassifier #For Classification
  clf = GradientBoostingClassifier(n_estimators=100, learning_rate=1.0, 
  max_depth=1)
  clf.fit(x_train, y_train)
  </code></pre>
  
  <p>This is where it gives the below error:</p>
  
  <pre><code>clf.fit(x_train, y_train)
  Traceback (most recent call last):
  
  File "&lt;ipython-input-425-9249b506d83f&gt;", line 1, in &lt;module&gt;
  clf.fit(x_train, y_train)
  
  File "C:\Anaconda3\lib\site-packages\sklearn\ensemble\gradient_boosting.py",  
  line 973, in fit
  X, y = check_X_y(X, y, accept_sparse=['csr', 'csc', 'coo'], dtype=DTYPE)
  
  File "C:\Anaconda3\lib\site-packages\sklearn\utils\validation.py", line 526,  
  in check_X_y
  y = column_or_1d(y, warn=True)
  
  File "C:\Anaconda3\lib\site-packages\sklearn\utils\validation.py", line 562,   
  in column_or_1d
  raise ValueError("bad input shape {0}".format(shape))
  
  ValueError: bad input shape (37533, 3)
  </code></pre>
  
  <p>The data is as follows:</p>
  
  <pre><code>print(x_train)
          No  Yes
  32912  1.0  0.0
  35665  1.0  0.0
  32436  1.0  0.0
  25885  1.0  0.0
  24896  1.0  0.0
  51734  1.0  0.0
  4235   1.0  0.0
  51171  1.0  0.0
  33221  0.0  1.0
  
  print(y_train)
         Fatal  Incident  Non-Fatal
  32912    0.0       0.0        1.0
  35665    0.0       0.0        1.0
  32436    0.0       0.0        1.0
  </code></pre>
  
  <p>Can you tell what is the problem with Gradient Boosting fit() function that it gives the error:
  ValueError: bad input shape (37533, 3)</p>