text: from sklearn import tree
  import csv
  import graphviz
  
  csvfile = list(csv.reader(open('featureflow.csv')))
  x=[]
  y=[]
  key_row=0
  for row in csvfile:
      if(key_row==len(csvfile)-1):
          break
      else:
          x.append(row[0:3])
          y.append(int(row[len(row)-1]))
      key_row += 1
  
  key=0
  for item in x:
      x[key]=map(float,item)
      key+=1
  
  print x[0],y[0]
  
  clf = tree.DecisionTreeClassifier()
  clf = clf.fit(x, y)
  res=clf.predict([[160,150,1000]])
  print res
  dot_data = tree.export_graphviz(clf, out_file=None,
                           feature_names=['avali','dovomi','sevomi'],
                           class_names=['1','0'],
                           filled=True, rounded=True,
                           special_characters=True)
  
  
  graph = graphviz.Source(dot_data)
  graph
  
  # dot -Tps tree.dot -o outfile.ps