new_contents: '''
  Created on 24 mai 2017
  
  @author: buissondiaz
  '''
  from numpy import genfromtxt
  import numpy as np
  dataset = genfromtxt('eggs.csv', delimiter=' ')
  
  X = dataset[:,2:11]
  y = dataset[:,1]
  print type(dataset[1,3])
  print type(dataset[1,10])
  print type(dataset[1,11])
  print np.asanyarray(X)
  print np.isfinite(X).all()
  from sklearn import metrics
  from sklearn.linear_model import LogisticRegression
  from sklearn.linear_model import LogisticRegression
  from sklearn.preprocessing import StandardScaler
  from sklearn.cross_validation import cross_val_score
  from sklearn.pipeline import Pipeline
  
  
  #X, y = dataset.load_train()
  
  raw_scaler = StandardScaler()
  raw_scaler.fit(X)
  X_scaled = raw_scaler.transform(X)
  print np.any(np.isnan(X_scaled))
  bad_indices = np.where(np.isinf(X_scaled))
  print "np.inf=", np.where(np.isnan(X))
  print "is.inf=", np.where(np.isinf(X))
  print "np.max=", np.max(abs(X))
  
  print(bad_indices)
  clf = LogisticRegression(C=0.03, class_weight='auto')
  print X_scaled
  clf.fit(np.nan_to_num(X), y)
  print(clf)
  
subject: Create model.py