随机森林不分类

Question

我在数据集（图像）上使用转移学习得到特征向量

X =
[[0.06381412 1.5189143  0.7007909  ... 0.22550535 0.56980544 0.07307615]
 [0.06381412 1.5189143  0.7007909  ... 0.22550535 0.56980544 0.07307615]
 [0.06381412 1.5189143  0.7007909  ... 0.22550535 0.56980544 0.07307615]
 ...
 [0.06381412 1.5189143  0.7007909  ... 0.22550535 0.56980544 0.07307615]
 [0.06381412 1.5189143  0.7007909  ... 0.22550535 0.56980544 0.07307615]
 [0.06381412 1.5189143  0.7007909  ... 0.22550535 0.56980544 0.07307615]]







imgs_train, imgs_test, y_train, y_test, = train_test_split(X, Y,test_size=0.33, random_state=42)                
Mrfc = RandomForestClassifier(n_estimators = 1000, 
                                 bootstrap = True,
                                 oob_score = True,
                                 criterion = 'gini', 
                                 max_features = 'auto',
                                 max_depth = dep,
                                 min_samples_split = int(3000), 
                                 min_samples_leaf = int(1000), 
                                 max_leaf_nodes = None,
                                 n_jobs=-1
                                )       
Mrfc.fit(imgs_train,y_train)
y_predict = Mrfc.predict(imgs_train)

y\u predict的输出均为零：

[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...]

Y包含标签（0或1） 模型无法做出预测。我能做什么

Answer 1

会不会是这样的，你的标签中有歪斜的类，所以全零的预测实际上给了你很高的精确度？在这种情况下，您可能需要尝试为您的RandomForestClassifier设置class\u weight=“balanced”