a5ad7f9408913bfbcdf3f110062b214a0a092869,src/skmultiflow/demos/_test_knn_adwin.py,,demo,#,11

Before Change

        // pipe.partial_fit(X, y, target_values=stream.get_targets())
        // pipe2.fit(X, y)

        knn.partial_fit(X, y, classes=stream.get_targets())
        compare.fit(X, y)
        first = False
    n_samples = 0
    max_samples = 10000
    my_corrects = 0
    compare_corrects = 0

    while n_samples < max_samples:
        if n_samples % (max_samples/20) == 0:
            logging.info("%s%%", str((n_samples//(max_samples/20)*5)))
        X, y = stream.next_sample()
        // my_pred = pipe.predict(X)
        my_pred = knn.predict(X)
        // my_pred = [1]
        if first:
            // pipe.partial_fit(X, y, target_values=stream.get_targets())
            // pipe.partial_fit(X, y, target_values=stream.get_targets())
            knn.partial_fit(X, y, classes=stream.get_targets())
            first = False
        else:
            // pipe.partial_fit(X, y)
            knn.partial_fit(X, y)

After Change

        // pipe.partial_fit(X, y, classes=stream.target_values)
        // pipe2.fit(X, y)

        knn.partial_fit(X, y, classes=stream.target_values)
        compare.fit(X, y)
        first = False
    n_samples = 0
    max_samples = 10000
    my_corrects = 0
    compare_corrects = 0

    while n_samples < max_samples:
        if n_samples % (max_samples/20) == 0:
            logging.info("%s%%", str((n_samples//(max_samples/20)*5)))
        X, y = stream.next_sample()
        // my_pred = pipe.predict(X)
        my_pred = knn.predict(X)
        // my_pred = [1]
        if first:
            // pipe.partial_fit(X, y, classes=stream.target_values)
            // pipe.partial_fit(X, y, classes=stream.target_values)
            knn.partial_fit(X, y, classes=stream.target_values)
            first = False
        else:
            // pipe.partial_fit(X, y)
            knn.partial_fit(X, y)

Instances