Hi Olivier,
Thanks for your info.I will follow it from now on. Details of traceback
are given below:
--Full traceback---
Fitting 3 folds for each of 10 candidates, totalling 30 fits
C:\Users\ssampathkumar\AppData\Local\Continuum\Anaconda3\lib\site-packages\sklearn\grid_sear
Please provide the full traceback. Without it it's impossible to tell
whether the problem is in scikit-learn or xgboost.
Also, please provide a minimal reproduction script as explained in:
http://scikit-learn.org/stable/faq.html#what-s-the-best-way-to-get-help-on-scikit-learn-usage
--
Olivier
_
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,
