被阻止 - ImportError：无法从“sklearn”导入名称

Question

我正在尝试运行下面的代码。

import numpy as np

import matplotlib.pyplot as plt

from sklearn.metrics import classification_report

from sklearn import cross_validation

from sklearn.tree import DecisionTreeClassifier

from utilities import visualize_classifier

# Load input data

input_file = 'data_decision_trees.txt'

data = np.loadtxt(input_file, delimiter=',')

X, y = data[:, :-1], data[:, -1]

# Separate input data into two classes based on labels

class_0 = np.array(X[y==0])

class_1 = np.array(X[y==1])

# Visualize input data

plt.figure()

plt.scatter(class_0[:, 0], class_0[:, 1], s=75, facecolors='black', 

        edgecolors='black', linewidth=1, marker='x')

plt.scatter(class_1[:, 0], class_1[:, 1], s=75, facecolors='white', 

        edgecolors='black', linewidth=1, marker='o')

plt.title('Input data')

# Split data into training and testing datasets 

X_train, X_test, y_train, y_test = cross_validation.train_test_split(

        X, y, test_size=0.25, random_state=5)

# Decision Trees classifier 

params = {'random_state': 0, 'max_depth': 4}

classifier = DecisionTreeClassifier(**params)

classifier.fit(X_train, y_train)

visualize_classifier(classifier, X_train, y_train, 'Training dataset')

y_test_pred = classifier.predict(X_test)

visualize_classifier(classifier, X_test, y_test, 'Test dataset')

# Evaluate classifier performance

class_names = ['Class-0', 'Class-1']

print("\n" + "#"*40)

print("\nClassifier performance on training dataset\n")

print(classification_report(y_train, classifier.predict(X_train), target_names=class_names))

print("#"*40 + "\n")

print("#"*40)

print("\nClassifier performance on test dataset\n")

print(classification_report(y_test, y_test_pred, target_names=class_names))

print("#"*40 + "\n")

plt.show()

错误发生在这一行：

from sklearn import cross_validation

我在 Anaconda 命令窗口中尝试了以下操作：

conda update scikit-learn

pip install -U scikit-learn

在这两种情况下，我都得到了“要求已经是最新的”的确认信息。我不确定为什么我在尝试运行脚本时会收到这些错误消息，因为所有 sklearn 的东西似乎都是最新的。还有什么我可以尝试的吗？这段代码肯定可以工作，但它会不断地绊倒自己。谢谢。

Answer 1

如果您的 sklearn 是最新的，则 sklearn.cross_validate 模块已被 sklearn.model_selection 弃用。尝试：from sklearn.model_selection import train_test_split