alfard

import pandas as pd
import numpy as np
from sklearn.metrics import roc_auc_score


#########################################################################################

NN_E=np.load('/home/alfard/Documents/Kaggle/Facebook-Robot/NN_E.npz')
NN_E=NN_E['arr_0']

alfard

import pandas as pd
import numpy as np
from sklearn import ensemble, feature_extraction, preprocessing

A=pd.read_pickle(('/home/alfard/Documents/Kaggle/Facebook-Robot/A.pk'))
#A = A.join(train[['outcome']], on='bidder_id')
A.shape

B=pd.read_pickle(('/home/alfard/Documents/Kaggle/Facebook-Robot/B.pk'))
#B=train[['bidder_id','outcome']]

alfard

import pandas as pd
import numpy as np
from sklearn import ensemble, feature_extraction, preprocessing

A=pd.read_pickle(('/home/alfard/Documents/Kaggle/Facebook-Robot/A.pk'))
#A = A.join(train[['outcome']], on='bidder_id')
A.shape

B=pd.read_pickle(('/home/alfard/Documents/Kaggle/Facebook-Robot/B.pk'))
#B=train[['bidder_id','outcome']]

alfard

import numpy as np
import random


class Node:
	def __init__(self,t,L,R,D,S,V,M,X):
		self.t=t  
		self.L=L
		self.R=R
		self.D=D

alfard

import numpy as np
import csv
import random

####TRAIN######################################################################
a=[]
 
f = open('/home/alfard/Documents/Kaggle/Loan/train20000.csv',"rb")
#f = open('/home/ubuntu/train_v2.csv',"rb")

alfard

import matplotlib.pyplot as plt
import datetime
import numpy as np

from ggplot import *

import pandas as pd

#####################################################################

alfard

import sys
import tweepy
import csv

#Code provenant de https://apps.twitter.com
consumer_key = '...........................'
consumer_secret = '...........................'
access_token = '...........................'
access_token_secret = '...........................'

alfard

import pandas as pd
import numpy as np
import csv
import random

a=[]

######################################################################### 

#f = open('/home/alfard/Documents/Kaggle/Facebook2/TrainClean.csv',"rb")

alfard

import pandas as pd
import numpy as np
import csv
import random


###########RECUPERATION DES RESULTATS############################################

#np.savez('/home/alfard/Documents/Kaggle/Facebook2/result.npz',RESULT)

alfard

stopwords=[' a ',
 ' about ',
 ' above ',
 ' above ',
 ' across ',
 ' after ',
 ' afterwards ',
 ' again ',
 ' against ',
 ' all ',