Question

我想保存并加载一个适合的随机森林分类器，但是我收到错误。

forest = RandomForestClassifier(n_estimators = 100, max_features = mf_val)
forest = forest.fit(L1[0:100], L2[0:100])
joblib.dump(forest, 'screening_forest/screening_forest.pkl')
forest2 = joblib.load('screening_forest/screening_forest.pkl')

错误是：

  File "C:\Users\mkolarek\Documents\other\TrackerResultAnalysis\ScreeningClassif
ier\ScreeningClassifier.py", line 67, in <module>
    forest2 = joblib.load('screening_forest/screening_forest.pkl')
  File "C:\Python27\lib\site-packages\sklearn\externals\joblib\numpy_pickle.py",
 line 425, in load
    obj = unpickler.load()
  File "C:\Python27\lib\pickle.py", line 858, in load
    dispatch[key](self)
  File "C:\Python27\lib\site-packages\sklearn\externals\joblib\numpy_pickle.py",
 line 285, in load_build
    Unpickler.load_build(self)
  File "C:\Python27\lib\pickle.py", line 1217, in load_build
    setstate(state)
  File "_tree.pyx", line 2280, in sklearn.tree._tree.Tree.__setstate__ (sklearn\
tree\_tree.c:18350)
ValueError: Did not recognise loaded array layout
Press any key to continue . . .

我是否必须初始化forest2或其他东西？

Answer 1

我用cPickle解决了它：

with open('screening_forest/screening_forest.pickle', 'wb') as f:
    cPickle.dump(forest, f)

with open('screening_forest/screening_forest.pickle', 'rb') as f:
    forest2 = cPickle.load(f)

但是，joblib解决方案也很有用。

Answer 2

这里是您可以尝试的方法：

model = RandomForestClassifier()

model.fit(data,lables)

import pickle

Model_file = 'model.pkl'

pickle.dump(model, open(Model_file, 'wb'))

'''Reloading the model
load the model from Saved file'''

loaded_model = pickle.load(open(Model_file, 'rb'))

保存随机森林

2 个答案: