shapelets算法python代码

以下是一个简单的 shapelets 算法的 Python 代码示例：

import numpy as np
from sklearn.utils import check_random_state

def generate_data(n_samples, n_features, n_classes, random_state=None):
    rng = check_random_state(random_state)
    X = rng.randn(n_samples, n_features)
    y = rng.randint(n_classes, size=n_samples)
    return X, y

def distance(x, y):
    return np.sqrt(np.sum((x - y) ** 2))

def find_shapelet(X, y):
    min_dist = np.inf
    best_shapelet = None
    for i in range(X.shape[1]):
        for j in range(X.shape[0]):
            for k in range(j + 1, X.shape[0]):
                dist = distance(X[j:j+i], X[k:k+i])
                if dist < min_dist:
                    min_dist = dist
                    best_shapelet = X[j:j+i]
    return best_shapelet

X, y = generate_data(n_samples=100, n_features=10, n_classes=2, random_state=42)
shapelet = find_shapelet(X, y)
print(shapelet)

这个代码演示了如何使用 shapelets 算法在一个随机生成的数据集中找到一个 shapelet。