generated from LufsX/Experiment-kNN
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@@ -47,19 +47,13 @@ from collections import Counter
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def classify(input_vector, dataSet, labels, k=3):
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"""使用 KNN 算法对输入样本进行分类。"""
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# 计算协方差矩阵和其逆矩阵
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cov_matrix = np.cov(dataSet, rowvar=False)
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inv_cov_matrix = np.linalg.inv(cov_matrix + 1e-5 * np.eye(cov_matrix.shape[0])) # 添加小常数以防止奇异矩阵
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# 计算马氏距离
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diffs = input_vector - dataSet
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distances = np.sqrt(np.einsum('ij,jk->i', diffs, np.dot(inv_cov_matrix, diffs.T)))
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distances = np.sum((input_vector - dataSet) ** 2, axis=1)
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sorted_indices = distances.argsort()
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k_nearest_distances = distances[sorted_indices[:k]]
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k_nearest_labels = labels[sorted_indices[:k]]
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# 计算权重(距离的倒数),避免除以零
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weights = 1 / (distances[sorted_indices[:k]] + 1e-5)
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weights = 1 / (k_nearest_distances + 1e-5)
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# 归一化权重
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weights /= weights.sum()
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