title: working with dataset in sklearn
body: <p>I have a dataset is in this format in .csv</p>
  
  <pre><code>id,interaction_flag,x_coordinate,y_coordinate,z_coordinate,hydrophobicity_kd,hydrophobicity_ww,hydrophobicity_hh,surface_tension,charge_cooh,charge_nh3,charge_r,alpha_helix,beta_strand,turn,van_der_walls,mol_wt,solublity  
  229810,1,-33.8675148907451,-110.273691995647,100.021824089754,0.129381338742408,0.129381338742408,0.129381338742408,57.9996957403639,2.20539553752535,9.55985801217038,4.47146044624688,1.08064908722114,1.20135902636915,0.611653144016251,145.232251521298,107.951643002026,21.5344036511141        
  229811,1,-26.9070290467923,-117.172163712053,106.980243932766,0.922048681541592,0.922048681541592,0.922048681541592,58.5383367139972,2.03983772819472,9.23210953346856,1.58401622717997,0.84178498985806,1.0387626774848,0.921703853955354,124.73630831643,84.1570182555755,10.7648600405665
  </code></pre>
  
  <p>I am trying to get Receiver Operating Characteristics (ROC) from this data using this link : <a href="http://scikit-learn.org/0.11/auto_examples/plot_roc.html" rel="nofollow">http://scikit-learn.org/0.11/auto_examples/plot_roc.html</a></p>
  
  <p>My target is interaction_flag column and test is all columns after interaction_flag.
  But, my program continue running in never ending state. </p>
  
  <p>When I run the test example given in that link, it runs within a moment.  </p>
  
  <p>Can anyone let me know what wrong I am doing? or do I need to so something else to load my data like iris?</p>
  
  <p>my code : </p>
  
  <pre><code>import numpy as np
  import pylab as pl
  from sklearn import svm, datasets
  from sklearn.utils import shuffle
  from sklearn.metrics import roc_curve, auc
  
  training = 'dataset/training_5000_col.csv'
  test = 'dataset/test_5000_col.csv'
  
  random_state = np.random.RandomState(0)
  
  # Import some data to play with
  #iris = datasets.load_iris()
  #X = iris.data
  #y = iris.target
  X = []
  y = []
  for line in open(training):
      z = line.rstrip().split(',')
  y.append(int(z[2]))
  tmp = []
  for a in range(5, 15):
      tmp.append(float(z[a]))
  X.append(tmp)
  X_train = np.array(X)
  y_train = np.array(y)
  
  
  
  X1 = []
  y1 = []
  for line in open(test):
  z = line.rstrip().split(',')
  y1.append(int(z[2]))
  tmp = []
  for a in range(5, 15):
      tmp.append(float(z[a]))
  X1.append(tmp)
  X_test = np.array(X1)
  y_test = np.array(y1)
  
  # Run classifier
  classifier = svm.SVC(kernel='linear', probability=True)
  probas_ = classifier.fit(X_train, y_train).predict_proba(X_test)
  
  # Compute ROC curve and area the curve
  fpr, tpr, thresholds = roc_curve(y_test, probas_[:, 1])
  print "y_test : ", y_test
  print "fpr : ", fpr
  print "tpr : ", tpr
  roc_auc = auc(fpr, tpr)
  print "Area under the ROC curve : %f" % roc_auc
  
  # Plot ROC curve
  pl.clf()
  pl.plot(fpr, tpr, label='ROC curve (area = %0.2f)' % roc_auc)
  pl.plot([0, 1], [0, 1], 'k--')
  pl.xlim([0.0, 1.0])
  pl.ylim([0.0, 1.0])
  pl.xlabel('False Positive Rate')
  pl.ylabel('True Positive Rate')
  pl.title('Receiver operating characteristic example')
  pl.legend(loc="lower right")
  pl.show()
  </code></pre>
  
  <p>my .csv file is at  : <a href="http://pastebin.com/iet5xQW2" rel="nofollow">http://pastebin.com/iet5xQW2</a>
  how I will plot roc with this .csv</p>