generated from LufsX/Challenge-kNN
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@@ -1,7 +1,5 @@
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# function.py
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pip install sklearn
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import numpy as np
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from sklearn.preprocessing import StandardScaler
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import numpy as np
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from numpy.linalg import inv
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"""
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挑战说明:
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@@ -58,11 +56,7 @@ def classify0(inX, dataSet, labels, k=4, cov_inv=None):
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if cov_inv is None:
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# 计算训练数据的协方差矩阵并求逆
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cov_matrix = np.cov(dataSet.T)
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cov_inv = inv(cov_matrix)
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# 计算待分类样本与所有训练样本之间的马氏距离
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# 注意:这里我们假设 inX 已经被适当地预处理(例如,通过 StandardScaler 归一化)
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# 并且 dataSet 也是用相同的预处理步骤处理的
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cov_inv = inv(cov_matrix)
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differences = dataSet - inX
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mahalanobis_distances = np.sqrt(np.sum(differences @ cov_inv @ differences.T, axis=1))
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