rsibi / epl-prediction-2017 Goto Github PK

Hi there, love the work you did on this project, was able to follow your guide to the core but i am getting errors in predicting the results for knn and XGB.

This is what i get:

ValueErrorTraceback (most recent call last)
in ()
----> 1 y_pred_XGB = clf_XGB.predict(X_predict)
2 y_pred_knn = clf_knn.predict(X_predict)

/usr/local/lib/python2.7/dist-packages/xgboost/sklearn.pyc in predict(self, data, output_margin, ntree_limit)
460
461 def predict(self, data, output_margin=False, ntree_limit=0):
--> 462 test_dmatrix = DMatrix(data, missing=self.missing)
463 class_probs = self.booster().predict(test_dmatrix,
464 output_margin=output_margin,

/usr/local/lib/python2.7/dist-packages/xgboost/core.pyc in init(self, data, label, missing, weight, silent, feature_names, feature_types)
253 data, feature_names, feature_types = _maybe_pandas_data(data,
254 feature_names,
--> 255 feature_types)
256 label = _maybe_pandas_label(label)
257

/usr/local/lib/python2.7/dist-packages/xgboost/core.pyc in _maybe_pandas_data(data, feature_names, feature_types)
179 msg = """DataFrame.dtypes for data must be int, float or bool.
180 Did not expect the data types in fields """
--> 181 raise ValueError(msg + ', '.join(bad_fields))
182
183 if feature_names is None:

ValueError: DataFrame.dtypes for data must be int, float or bool.
Did not expect the data types in fields HAS, HDS, AAS, ADS

i have tried to convert the data frame to .astype(np.float64) but it is still not working please help.

Thanks.