old_contents: import numpy as np
  import pandas as pd
  import sys
  import os
  from sklearn.externals import joblib
  from sklearn.ensemble import RandomForestClassifier
  
  scriptpath = os.path.dirname(os.path.realpath(sys.argv[0])) + '/../'
  sys.path.append(os.path.abspath(scriptpath))
  import utils
  
  parameter_str = '_'.join(['top', str(utils.k), 'cw', str(utils.click_weight), 'year', utils.train_year])
  cforest = joblib.load(utils.model_path + 'rf_all_without_time_' + parameter_str +'.pkl')
  
  test = joblib.load(utils.processed_data_path + 'test_all_' + parameter_str +'.pkl')
  X_test = test.ix[:,1:]
  
  print "predict RandomForest Classifier..."
  
  probs = cforest.predict_proba(X_test)
  sorted_index = np.argsort(-np.array(probs))[:,:5]
  
  result = pd.DataFrame(columns = {'hotel_cluster'})
  
  result['hotel_cluster'] = np.array([np.array_str(sorted_index[i])[1:-1] for i in range(sorted_index.shape[0])])
  
  result.hotel_cluster.to_csv(utils.model_path + 
  	'results/submission_rf_all_without_time_' + parameter_str + '.csv', header=True, index_label='id')
  
  
  
new_contents: import numpy as np
  import pandas as pd
  import sys
  import os
  from sklearn.externals import joblib
  from sklearn.ensemble import RandomForestClassifier
  
  scriptpath = os.path.dirname(os.path.realpath(sys.argv[0])) + '/../'
  sys.path.append(os.path.abspath(scriptpath))
  import utils
  
  parameter_str = '_'.join(['top', str(utils.k), 'cw', str(utils.click_weight), 'year', utils.train_year])
  cforest = joblib.load(utils.model_path + 'rf_all_without_time_' + parameter_str +'.pkl')
  
  test = joblib.load(utils.processed_data_path + 'test_all_' + parameter_str +'.pkl')
  #X_test = test.ix[:,1:]
  X_test = test.ix[:9,1:]
  
  X_test.fillna(-1, inplace=True)
  
  print "predict RandomForest Classifier..."
  
  probs = cforest.predict_proba(X_test)
  sorted_index = np.argsort(-np.array(probs))[:,:5]
  
  result = pd.DataFrame(columns = {'hotel_cluster'})
  
  result['hotel_cluster'] = np.array([np.array_str(sorted_index[i])[1:-1] for i in range(sorted_index.shape[0])])
  
  result.hotel_cluster.to_csv(utils.model_path + 
  	'results/submission_rf_all_without_time_' + parameter_str + '.csv', header=True, index_label='id')
  
  
  
subject: Handle missing value in predit rf