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luokn · May 22, 2022 · c8fe317 · c8fe317
1 parent a1ab0a4
commit c8fe317
Showing 1 changed file with 9 additions and 7 deletions.
diff --git a/src/adaboost.py b/src/adaboost.py
@@ -57,13 +57,15 @@ def __init__(self, lr: float):
 
     def fit(self, X: np.ndarray, y: np.ndarray, weights: np.ndarray):
         min_error = float("inf")  # 最小带权误差
-        for f, x in enumerate(X.T):
+        for feature, x in enumerate(X.T):
             for threshold in np.arange(np.min(x) - self.lr, np.max(x) + self.lr, self.lr):
-                for sign in [1, -1]:
-                    # 取分类错误的样本权重求和
-                    error = np.sum(weights[np.where(x > threshold, sign, -sign) != y])
-                    if error < min_error:
-                        self.feature, self.threshold, self.sign, min_error = f, threshold, sign, error
+                # 取分类错误的样本权重求和
+                pos_error = np.sum(weights[np.where(x > threshold, 1, -1) != y])
+                if pos_error < min_error:
+                    min_error, self.feature, self.threshold, self.sign = pos_error, feature, threshold, 1
+                neg_error = 1 - pos_error
+                if neg_error < min_error:
+                    min_error, self.feature, self.threshold, self.sign = neg_error, feature, threshold, -1
         return min_error
 
     def __call__(self, X: np.ndarray) -> np.ndarray:
@@ -79,7 +81,7 @@ def load_data(n_samples_per_class=500):
     )
     y = np.array([1] * n_samples_per_class + [-1] * n_samples_per_class)
 
-    training_set, test_set = np.split(np.random.permutation(len(X)), [int(len(X) * 0.6)])
+    training_set, test_set = np.split(np.random.permutation(len(X)), [int(len(X) * 0.8)])
     return X, y, training_set, test_set