ae32c93dda05262199bfa0a5b144e4b8990145b2,tslearn/docs/examples/plot_sax_mindist_knn.py,,,#,82

Before Change

    start = time.time()
    knn.fit(X_train, y_train)
    predictions = knn.predict(X_test)
    acc_euclidean = accuracy_score(y_test, predictions)
    time_euclidean = time.time() - start

    accuracies[dataset] = (acc_sax, acc_euclidean)
    times[dataset] = (time_sax, time_euclidean)

After Change

numpy.random.seed(0)
// Generate a random walk time series
data_loader = UCR_UEA_datasets()
datasets = [
    ("SyntheticControl", 16),
    ("GunPoint", 64),
    ("FaceFour", 128),
    ("Lightning2", 256),
    ("Lightning7", 128),
    ("ECG200", 32),
    ("Plane", 64),
    ("Car", 256),
    ("Beef", 128),
    ("Coffee", 128),
    ("OliveOil", 256)
]

accuracies = {}
times = {}
for dataset, w in datasets:

Instances