更新 function.py

function.py

@@ -42,11 +42,22 @@ def classify(input_vector, dataSet, labels, k=2):
     - int: 预测的分类标签。
     """
     num_samples = dataSet.shape[0]
-    diffs = np.tile(input_vector, (num_samples, 1)) - dataSet
-    distances = np.sum(diffs**2, axis=1)**0.5
+    mu = np.mean(dataSet, axis = 0)
+    cov = np.cov(dataSet.T)
+    try:
+        inv_cov = np.linalg.inv(cov)
+    except np.linalg.LinAlgError:
+        # 如果协方差矩阵不可逆，使用伪逆
+        inv_cov = np.linalg.pinv(cov)
+    distances = []
+    for i in range(num_samples):
+        diff = (input_vector - dataSet[i])
+        distance = np.sqrt(np.dot(np.dot(diff, inv_cov), diff.T))
+        distances.append(distance)
+    distances = np.array(distances)
     sorted_indices = np.argsort(distances)
     k_nearest_labels = [labels[i] for i in sorted_indices[:k]]
-    unique_labels, counts = np.unique(k_nearest_labels, return_counts=True)
+    unique_labels, counts = np.unique(k_nearest_labels, return_counts = True)
     return unique_labels[np.argmax(counts)]