Overview

Groups consisting of instances with similar time series.

Example

from sklearn.model_selection import train_test_split
from sktime.clustering.k_means import TimeSeriesKMeans
from sktime.clustering.utils.plotting._plot_partitions import plot_cluster_algorithm
from sktime.datasets import load_arrow_head

Dataset

The arrowhead data consists of outlines of the images of arrowheads. The shapes of the projectile points are converted into a time series using the angle-based method. The classification of projectile points is an important topic in anthropology. The classes are based on shape distinctions such as the presence and location of a notch in the arrow. The problem in the repository is a length normalised version of that used in Ye09shapelets. The three classes are called “Avonlea”, “Clovis” and “Mix”.”

Dataset details: here. Dimensionality: univariate Series length: 251 Train cases: 36 Test cases: 175 Number of classes: 3.

X, y = load_arrow_head()
X_train, X_test, y_train, y_test = train_test_split(X, y)

k_means = TimeSeriesKMeans(n_clusters=5, init_algorithm="forgy", metric="dtw")
k_means.fit(X_train)
plot_cluster_algorithm(k_means, X_test, k_means.n_clusters)