更新 function.py

function.py

@@ -54,7 +54,8 @@ def classify0(inX, dataSet, labels, k=3):
     - int: 预测的分类标签。
     """
     # 确保输入样本 inX 是二维数组
-    inX = np.mat(inX)
+    inX = np.atleast_2d(inX)
+    
     # 计算样本数量和特征数量
     numSamples, numFeatures = dataSet.shape
     
@@ -66,8 +67,9 @@ def classify0(inX, dataSet, labels, k=3):
     covMat += np.eye(numFeatures) * 0.0001
     
     # 计算待分类样本与训练集中每个样本的马氏距离
-    inXMinusMean = inX - meanVals
-    dist = np.sqrt(np.sum(inXMinusMean * np.linalg.inv(covMat) * inXMinusMean.T))
+    diffMat = dataSet - meanVals
+    invCovMat = np.linalg.inv(covMat)
+    dist = np.sum(np.dot(diffMat, invCovMat) * diffMat, axis=1)
     
     # 获取距离最近的k个样本的索引
     sortedDistIndices = np.argsort(dist)