title: Can't get SVC Score function to work
body: <p>I am trying to run this machine learning platform and I get the following error: </p>
  
  <pre><code>ValueError: X.shape[1] = 574 should be equal to 11, the number of features at training time
  </code></pre>
  
  <p>My Code:</p>
  
  <pre><code>from pylab import *
  from sklearn.svm import SVC
  from sklearn.ensemble import RandomForestClassifier
  import numpy as np
  
  X = list ()
  Y = list ()
  validationX = list ()
  validationY = list ()
  file = open ('C:\\Users\\User\\Desktop\\csci4113\\project1\\whitewineTraining.txt','r')
  for eachline in file:
      strArray = eachline.split(";")
      row = list ()
      for i in range(len(strArray) - 1):
          row.append(float(strArray[i])) 
      X.append(row)
      if (int(strArray[-1]) &gt; 6):
          Y.append(1)
      else:
          Y.append(0)
  file2 = open ('C:\\Users\\User\\Desktop\\csci4113\\project1\\whitewineValidation.txt', 'r')
  for eachline in file2:
      strArray = eachline.split(";")
      row2 = list ()
      for i in range(len(strArray) - 1):
          row2.append(float(strArray[i])) 
      validationX.append(row2)      
      if (int(strArray[-1]) &gt; 6):
          validationY.append(1)
      else:
          validationY.append(0)
  
  X = np.array(X)
  print (X)
  Y = np.array(Y)
  print (Y)
  validationX = np.array(validationX)
  validationY = np.array(validationY)
  
  clf = svm.SVC()
  clf.fit(X,Y)
  result = clf.predict(validationX)
  clf.score(result, validationY)
  </code></pre>
  
  <p>The goal of the program is to to build a model from the fit() command where we can use it to compare to a validation set in validationY and see the validity of our machine learning model. Here is the rest of the console output: keep in mind X is confusingly a 11x574 array!</p>
  
  <pre><code>[[  7.           0.27         0.36       ...,   3.           0.45         8.8       ]
   [  6.3          0.3          0.34       ...,   3.3          0.49         9.5       ]
   [  8.1          0.28         0.4        ...,   3.26         0.44        10.1       ]
   ..., 
   [  6.3          0.28         0.22       ...,   3.           0.33        10.6       ]
   [  7.4          0.16         0.33       ...,   3.04         0.68        10.5       ]
   [  8.4          0.27         0.3        ...,   2.89         0.3
     11.46666667]]
  [0 0 0 ..., 0 1 0]
  C:\Users\User\Anaconda3\lib\site-packages\sklearn\utils\validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
    DeprecationWarning)
  Traceback (most recent call last):
  
    File "&lt;ipython-input-68-31c649fe24b3&gt;", line 1, in &lt;module&gt;
      runfile('C:/Users/User/Desktop/csci4113/project1/program1.py', wdir='C:/Users/User/Desktop/csci4113/project1')
  
    File "C:\Users\User\Anaconda3\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 714, in runfile
      execfile(filename, namespace)
  
    File "C:\Users\User\Anaconda3\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 89, in execfile
      exec(compile(f.read(), filename, 'exec'), namespace)
  
    File "C:/Users/User/Desktop/csci4113/project1/program1.py", line 43, in &lt;module&gt;
      clf.score(result, validationY)
  
    File "C:\Users\User\Anaconda3\lib\site-packages\sklearn\base.py", line 310, in score
      return accuracy_score(y, self.predict(X), sample_weight=sample_weight)
  
    File "C:\Users\User\Anaconda3\lib\site-packages\sklearn\svm\base.py", line 568, in predict
      y = super(BaseSVC, self).predict(X)
  
    File "C:\Users\User\Anaconda3\lib\site-packages\sklearn\svm\base.py", line 305, in predict
      X = self._validate_for_predict(X)
  
    File "C:\Users\User\Anaconda3\lib\site-packages\sklearn\svm\base.py", line 474, in _validate_for_predict
      (n_features, self.shape_fit_[1]))
  
  ValueError: X.shape[1] = 574 should be equal to 11, the number of features at training time
  
  
  runfile('C:/Users/User/Desktop/csci4113/project1/program1.py', wdir='C:/Users/User/Desktop/csci4113/project1')
  10
  [[  7.           0.27         0.36       ...,   3.           0.45         8.8       ]
   [  6.3          0.3          0.34       ...,   3.3          0.49         9.5       ]
   [  8.1          0.28         0.4        ...,   3.26         0.44        10.1       ]
   ..., 
   [  6.3          0.28         0.22       ...,   3.           0.33        10.6       ]
   [  7.4          0.16         0.33       ...,   3.04         0.68        10.5       ]
   [  8.4          0.27         0.3        ...,   2.89         0.3
     11.46666667]]
  [0 0 0 ..., 0 1 0]
  C:\Users\User\Anaconda3\lib\site-packages\sklearn\utils\validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.
    DeprecationWarning)
  Traceback (most recent call last):
  
    File "&lt;ipython-input-69-31c649fe24b3&gt;", line 1, in &lt;module&gt;
      runfile('C:/Users/User/Desktop/csci4113/project1/program1.py', wdir='C:/Users/User/Desktop/csci4113/project1')
  
    File "C:\Users\User\Anaconda3\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 714, in runfile
      execfile(filename, namespace)
  
    File "C:\Users\User\Anaconda3\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 89, in execfile
      exec(compile(f.read(), filename, 'exec'), namespace)
  
    File "C:/Users/User/Desktop/csci4113/project1/program1.py", line 46, in &lt;module&gt;
      clf.score(result, validationY)
  
    File "C:\Users\User\Anaconda3\lib\site-packages\sklearn\base.py", line 310, in score
      return accuracy_score(y, self.predict(X), sample_weight=sample_weight)
  
    File "C:\Users\User\Anaconda3\lib\site-packages\sklearn\svm\base.py", line 568, in predict
      y = super(BaseSVC, self).predict(X)
  
    File "C:\Users\User\Anaconda3\lib\site-packages\sklearn\svm\base.py", line 305, in predict
      X = self._validate_for_predict(X)
  
    File "C:\Users\User\Anaconda3\lib\site-packages\sklearn\svm\base.py", line 474, in _validate_for_predict
      (n_features, self.shape_fit_[1]))``
  </code></pre>