相关疑难解决方法(0)

我无法从sklearn库中导入cross_validation；我使用sklearn版本0.20.0

from sklearn import cross_validation

稍后在代码中：

features_train, features_test, labels_train, labels_test = cross_validation.train_test_split(word_data, authors, test_size=0.1, random_state=42)

错误：

Traceback (most recent call last):
  File "D:\me\M.Sc\Udacity_ML_course\ud120-projects-  master\naive_bayes\nb_author_id.py", line 16, in <module>
    from email_preprocess import preprocess
  File "../tools/email_preprocess.py", line 8, in <module>
    from sklearn import cross_validation
ImportError: cannot import name cross_validation

我正在尝试进行交叉验证,我遇到了一个错误,上面写着:"发现输入变量的样本数量不一致:[18,1]"

我在pandas数据框(df)中使用不同的列作为功能,最后一列作为标签.这来自加州大学欧文分校的机器学习库.导入我过去使用的交叉验证包时,我收到一个可能已经折旧的错误.我将运行决策树,SVM和K-NN.

我的代码是这样的:

feature = [df['age'], df['job'], df['marital'], df['education'], df['default'], df['housing'], df['loan'], df['contact'],
       df['month'], df['day_of_week'], df['campaign'], df['pdays'], df['previous'], df['emp.var.rate'], df['cons.price.idx'],
       df['cons.conf.idx'], df['euribor3m'], df['nr.employed']]
label = [df['y']]

from sklearn.cross_validation import train_test_split
from sklearn.model_selection import cross_val_score
# Model Training 
x = feature[:]
y = label
x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.5)

任何帮助都会很棒!