delete hadoop conf

demo/binary_classification/mushroom.hadoop.conf

@@ -1,31 +0,0 @@
-# General Parameters, see comment for each definition
-# choose the booster, can be gbtree or gblinear
-booster = gbtree
-# choose logistic regression loss function for binary classification
-objective = binary:logistic
-
-# Tree Booster Parameters
-# step size shrinkage
-eta = 1.0 
-# minimum loss reduction required to make a further partition
-gamma = 1.0 
-# minimum sum of instance weight(hessian) needed in a child
-min_child_weight = 1 
-# maximum depth of a tree
-max_depth = 3 
-
-# Task Parameters
-# the number of round to do boosting
-num_round = 2
-# 0 means do not save any model except the final round model
-save_period = 0 
-# The path of training data
-data = "agaricus.txt.train" 
-
-# The following parameters are not supported by xgboost running in hadoop yet!
-# The path of validation data, used to monitor training process, here [test] sets name of the validation set
-#eval[test] = "agaricus.txt.test" 
-# evaluate on training data as well each round
-#eval_train = 1
-# The path of test data 
-#test:data = "agaricus.txt.test"