I am using KNeighborsClassifier and trying to obtain probabilistic output.
But for many of the test sets I am getting equal probability for all class.
>>>X_train, X_test, y_train, y_test =
cross_validation.train_test_split(iris.data, iris.target, test_size=0.4,
random_state=0)
>>>clf = KNeighborsClassifier(n_neighbors=4).fit(X_train, y_train)
>>>clf.predict_proba(X_test)
#An example output
[ 0. 0.5 0.5 ]
[ 0. 0.5 0.5 ]
[ 0. 1. 0. ]
Do the prediction of class label via function .predict in
KNeighborsClassifier use .predict_proba ?
In my another data-set the probability values for two particular classes
are most of the time equal (as shown in the example).
How do I break the tie in such cases?
Thanks
--
Sheila
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