@ignore_warnings // Warnings are raised by decision function
def check_classifiers_train(name, classifier_orig, readonly_memmap=False):
// Generate some random walk blobs, shuffle them and normalize them
X_m, y_m = random_walk_blobs(n_ts_per_blob=25, random_state=42,
n_blobs=3, noise_level=0.1, sz=75)
X_m, y_m = shuffle(X_m, y_m, random_state=7)
X_m = TimeSeriesScalerMeanVariance().fit_transform(X_m)
After Change
@ignore_warnings // Warnings are raised by decision function
def check_classifiers_train(name, classifier_orig, readonly_memmap=False):
// Generate some random walk blobs, shuffle them and normalize them
X_m, y_m = _create_small_ts_dataset()
X_m, y_m = shuffle(X_m, y_m, random_state=7)
X_m = TimeSeriesScalerMeanVariance().fit_transform(X_m)