RandomForest IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices

Question

我正在与 sklearn 合作 RandomForestClassifier:

class RandomForest(RandomForestClassifier):

    def fit(self, x, y):
        self.unique_train_y,  y_classes = transform_y_vectors_in_classes(y)
        return RandomForestClassifier.fit(self, x, y_classes)

    def predict(self, x):
        y_classes = RandomForestClassifier.predict(self, x)
        predictions = transform_classes_in_y_vectors(y_classes, self.unique_train_y)
        return predictions

    def transform_classes_in_y_vectors(y_classes, unique_train_y):
        cyr = [unique_train_y[predicted_index] for predicted_index in y_classes]
        predictions = np.array(float(cyr))
        return predictions

我收到此错误消息：

IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices

Answer 1

似乎 y_classes 包含的值不是有效索引。

当您尝试使用 predicted_index 访问 unique_train_y 时，您会遇到异常，因为 predicted_index 不是您想象的那样。

尝试执行以下代码：

cyr = [unique_train_y[predicted_index] for predicted_index in range(len(y_classes))] 
# assuming unique_train_y is a list and predicted_index should be integer.

RandomForest IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices

RandomForest IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices

python

numpy

classification

random-forest

scikit-learn