generated from LufsX/Experiment-kNN
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@@ -70,7 +70,7 @@ def classify_mahalanobis(input_vector, dataSet, labels, k=1):
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count = Counter(k_nearest_labels)
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# 返回数量最多的类别标签
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return count.most_common(1)[0][0]
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return count.most_common(1)[0][0]
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def load_dataset(directory):
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"""加载数据集中的图像,并将其转换为特征向量和标签。"""
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@@ -145,4 +145,4 @@ if __name__ == "__main__":
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train_labels,
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)
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print(f"预测的标签: {predicted_label}")
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print(f"预测的标签: {predicted_label}")
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