Question

尽管有很多关于错误ValueError: negative dimensions are not allowed的问题线程我找不到我的问题的答案

使用SGDclassifer训练机器学习模型后

clf=linear_model.SGDClassifier(loss='log',random_state=20000,verbose=1,class_weight='balanced')
model=clf.fit(X,Y)

X的维数是（1651880,246177）

下面的代码有效，即在保存模型对象和使用模型进行预测时

joblib.dump(model, 'trainedmodel.pkl',compress=3)

prediction_result=model.predict(x_test)

但是在加载保存的模型时出错

model = joblib.load('trainedmodel.pkl')

下面是错误消息请帮我解决。

  File "C:\Users\Taxonomy\AppData\Roaming\Python\Python36\site-packages\sklearn\externals\joblib\numpy_pickle.py", line 598, in load
    obj = _unpickle(fobj, filename, mmap_mode)

  File "C:\Users\Taxonomy\AppData\Roaming\Python\Python36\site-packages\sklearn\externals\joblib\numpy_pickle.py", line 526, in _unpickle
    obj = unpickler.load()

  File "C:\Users\Taxonomy\Anaconda3\lib\pickle.py", line 1050, in load
    dispatch[key[0]](self)

  File "C:\Users\Taxonomy\AppData\Roaming\Python\Python36\site-packages\sklearn\externals\joblib\numpy_pickle.py", line 352, in load_build
    self.stack.append(array_wrapper.read(self))

  File "C:\Users\Taxonomy\AppData\Roaming\Python\Python36\site-packages\sklearn\externals\joblib\numpy_pickle.py", line 195, in read
    array = self.read_array(unpickler)

  File "C:\Users\Taxonomy\AppData\Roaming\Python\Python36\site-packages\sklearn\externals\joblib\numpy_pickle.py", line 141, in read_array
    array = unpickler.np.empty(count, dtype=self.dtype)

ValueError: negative dimensions are not allowed

Answer 1

尝试使用协议4转储模型。

来自python的泡菜docs：

协议版本4已在Python 3.4中添加。它增加了对大对象，腌制更多种类的对象以及某些数据格式优化。有关改进的信息，请参考PEP 3154 由协议4带来。

ValueError：加载.pkl文件时不允许使用负尺寸

1 个答案: