形状不匹配：无法将对象广播到单个形状如何解决python中的此类错误？

Posted 2023-03-12

【中文标题】形状不匹配：无法将对象广播到单个形状如何解决python中的此类错误？

【英文标题】：shape mismatch: objects cannot be broadcast to a single shape how to solve this type of error in python?

【发布时间】：2021-08-06 19:18:38

【问题描述】：

如何在python中解决这种类型的错误？？

“ValueError：形状不匹配：对象不能广播到单个形状”，我​​的代码是：

代码：

X_train, X_test, y_train, y_test = train_test_split(
    cancer.data, cancer.target, random_state=0)
forest = RandomForestClassifier(n_estimators=100, random_state=0)
forest.fit(X_train, y_train)

print("Accuracy on training set: :.3f".format(forest.score(X_train, y_train)))
print("Accuracy on test set: :.3f".format(forest.score(X_test, y_test)))
plot_feature_importances_cancer(forest)

【参考方案1】：

我不确定你在哪里得到错误。 我可以使用您的代码运行它，但请尝试复制以下内容。

from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split
from sklearn.datasets import load_breast_cancer
import matplotlib.pyplot as plt

def plot_feature_importances_cancer(model):
    n_features = cancer.data.shape[1]
    plt.barh(range(n_features), model.feature_importances_, align='center')
    plt.yticks(np.arange(n_features),  cancer.feature_names)
    plt.xlabel("Feature importtances")
    plt.ylabel("Feature")

cancer = load_breast_cancer()

X_train, X_test, y_train, y_test = train_test_split(
    cancer.data, cancer.target, random_state=0)
forest = RandomForestClassifier(n_estimators=100, random_state=0)
forest.fit(X_train, y_train)

print("Accuracy on training set: :.3f".format(forest.score(X_train, y_train)))
print("Accuracy on test set: :.3f".format(forest.score(X_test, y_test)))

plot_feature_importances_cancer(forest)

【讨论】：

谢谢。运行到代码时出现这个错误：plot_feature_importances_cancer(forest)，你知道为什么

可能是运行 matplotlib 时 x 轴和 y 轴的长度不均匀。你可以在函数代码中运行print和shape，边走边检查：D