小编abb*_*han的帖子

我正在尝试运行本教程中的代码。我已将代码和数据集放在同一目录中，但仍然出现以下错误。

FileNotFoundError                         Traceback (most recent call last)
<ipython-input-6-5f5284db0527> in <module>()
     39 # extract features from all images
     40 directory = 'Flicker8k'
---> 41 features = extract_features(directory)
     42 print('Extracted Features: %d' % len(features))
     43 # save to file

<ipython-input-6-5f5284db0527> in extract_features(directory)
     18         # extract features from each photo
     19         features = dict()
---> 20         for name in listdir(directory):
     21                 # load an image from file
     22                 filename = directory + '/' + name

**FileNotFoundError: [WinError 3] The system cannot …

我正在运行多标签分类1的[代码]。如何修复未定义“ X_train”的NameError。下面给出了python代码。

import scipy
from scipy.io import arff
data, meta = scipy.io.arff.loadarff('./yeast/yeast-train.arff')
from sklearn.datasets import make_multilabel_classification

# this will generate a random multi-label dataset
X, y = make_multilabel_classification(sparse = True, n_labels = 20,
return_indicator = 'sparse', allow_unlabeled = False)

# using binary relevance
from skmultilearn.problem_transform import BinaryRelevance
from sklearn.naive_bayes import GaussianNB

# initialize binary relevance multi-label classifier
# with a gaussian naive bayes base classifier
classifier = BinaryRelevance(GaussianNB())

# train
classifier.fit(X_train, y_train)

# predict
predictions = classifier.predict(X_test)

from …