new_contents: 
  
  import numpy as np 
  
  import pandas as pd 
  
  import seaborn as sns
  
  from sklearn.neighbors import KNeighborsClassifier
   
  from sklearn import metrics
  
  from ClassifierWrapper import ClassifierWrapper
  
  from sklearn.ensemble import RandomForestClassifier
  
  from sklearn.cross_validation import train_test_split 
  
  from sklearn.metrics import confusion_matrix
  
  #Below the Data Set is being read (Replace the Path with the your path)
  
  
  Data=pd.read_csv('PATH OF YOUR CSV')
  
  
  olist=list(Data.select_dtypes(['object'])) 
  # Selecting the Columns of OBJECT type
  
  
  for col in olist:
   # Converting the OBJECT type to INTEGER type
  	Data[col]=Data[col].astype('category').cat.codes
  
  X=Data.drop("left",axis=1) 
  # Loading the ATTRIBUTE columns 
  
  
  Y=Data["left"].astype('category') 
  # Loading the TARGET column
  
  
  from sklearn.cross_validation import train_test_split
  
  X_train,X_test,Y_train,Y_test=train_test_split(X,Y,random_state=3) 
  # Splitting the DATA
  
  
  kn =KNeighborsClassifier(n_neighbors=1) 
  # Instanciating KNNEIGHBOURS Class
  
  
  cw = ClassifierWrapper(kn,X_train,X_test,Y_train,Y_test)
   
  # 
  Calling the Wrapper Class
  
subject: Add files via upload