i know, working on it ;)



Alexandre Gramfort <notifications@github.com> schrieb:

>> +    from sklearn.cross_validation import train_test_split
>> +    X_train, X_test, y_train, y_test = train_test_split(X, y)
>> +
>> +    # learn a k-nearest neighbor classificaton model
>> +    from sklearn.neighbors import KNeighborsClassifier
>> +    knn = KNeighborsClassifier(n_neighbors=3)
>> +    knn.fit(X_train, y_train)
>> +
>> +    KNeighborsClassifier(algorithm='auto', leaf_size=30,
>n_neighbors=3, p=2,
>> +               weights='uniform')
>> +    
>> +    # apply the model to test data
>> +    knn.predict(X_test)
>> +
>> +    array([0, 0, 0, 1, 0, 0, 1, 0, 2, 1, 0, 0, 2, 2, 0, 0, 2, 1, 0,
>0, 1, 0, 0,
>> +           2, 1, 1, 0, 2, 2, 2, 0, 0, 0, 1, 1, 2, 2, 1])
>
>this looks weird unless you add some >>>
>
>---
>Reply to this email directly or view it on GitHub:
>https://github.com/scikit-learn/scikit-learn/pull/1784/files#r3405777

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