[scikit-learn] XGboost Classifier error

[Startup Hire]

Hi!,

I am trying to use XGBoost Classifer in RandomizedSearchCV as follows:


clf = xgb.XGBClassifier()

random_search_sg = RandomizedSearchCV(clf, param_distributions=params_dist,
                                   n_iter=n_iter_search,
                                   scoring=kappa_scorer,
                                   verbose=3,
                                   error_score=-1,
                                   fit_params=fit_params,
                                   n_jobs=-1)

start = time()
random_search_sg.fit(scaled_data, a_l)


scaled_data = (0, 0) 4.53937223364

  (0, 1)	4.08089927979
  (0, 2)	5.08534158523
  (0, 3)	0.900022077306
  (0, 4)	0.582895703409
  (0, 5)	3.52674131829
  (0, 6)	2.00912587286
  (0, 8)	1.06039501135
  (0, 9)	4.8956331357
  (0, 11)	1.51595206264
  (0, 13)	3.00108387862
  (0, 14)	0.0
  (1, 0)	1.51312407788
  (1, 1)	1.36029975993
  (1, 2)	2.54267079261
  (1, 3)	1.36638272336
  (1, 4)	0.0225891281189
  (1, 5)	3.52674131829




a_l = [1 0 0 ..., 0 0 0] (after using ravel)


I am getting the error
Python int too large to convert to C long
<http://stackoverflow.com/questions/22114088/overflowerror-python-int-too-large-to-convert-to-c-long>
 while fitting the data using random_search_sg

How to resolve this? Is this related to the formats of scaled data and a_l
?


Regards,
Sanant
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