我在分类讨论线程中的帖子时使用了pystruct Python模块来解决结构化学习问题，并且在尝试培训OneSlackSSVM与LinearChainCRF结合使用时遇到了一个问题。我正在跟踪OCR example from the docs，但似乎无法在SSVM上调用.fit()方法。这是我得到的错误：
Traceback (most recent call last):
File "<ipython-input-47-da804d135818>", line 1, in <module>
ssvm.fit(X_train, y_train)
File "/Users/kylefth/anaconda/lib/python2.7/site-
packages/pystruct/learners/one_slack_ssvm.py", line 429, in fit
joint_feature_gt = self.model.batch_joint_feature(X, Y)
File "/Users/kylefth/anaconda/lib/python2.7/site-
packages/pystruct/models/base.py", line 40, in batch_joint_feature
joint_feature_ += self.joint_feature(x, y)
File "/Users/kylefth/anaconda/lib/python2.7/site-
packages/pystruct/models/graph_crf.py", line 197, in joint_feature
unary_marginals[gx, y] = 1
IndexError: index 7 is out of bounds for axis 1 with size 7
以下是我编写的代码。我已经厌倦了像docs示例中那样构造数据，其中的整体数据结构是一个
dict，其中键分别是data，labels和folds。from pystruct.models import LinearChainCRF
from pystruct.learners import OneSlackSSVM
# Printing out keys of overall data structure
print threads.keys()
>>> ['folds', 'labels', 'data']
# Creating instances of models
crf = LinearChainCRF()
ssvm = OneSlackSSVM(model=crf)
# Splitting up data into training and test sets as in example
X, y, folds = threads['data'], threads['labels'], threads['folds']
X_train, X_test = X[folds == 1], X[folds != 1]
y_train, y_test = y[folds == 1], y[folds != 1]
# Print out dimensions of first element in data and labels
print X[0].shape, y[0].shape
>>> (8, 211), (8,)
# Fitting the ssvm model
ssvm.fit(X_train, y_train)
>>> see error above
尝试拟合模型后，直接得到上述错误。
X_train，X_test，y_train和y_test的所有实例都有211列，并且所有标签尺寸似乎都与其相应的训练和测试数据相匹配。任何帮助将不胜感激。 最佳答案
我认为您所做的一切都是正确的，这是https://github.com/pystruct/pystruct/issues/114。
您的标签y必须从0到n_labels开始。我想你的从1开始。