正在尝试保存随机森林模型。
所有的方法都失败了:
self.model = RandomForestClassifier(n_estimators=n_estimators,criterion='entropy', min_samples_leaf=2, max_depth=15,min_samples_split=5, max_features=None, n_jobs=-1, random_state=555)
def save_model(self, fname):
with open(fname,'wb') as f :
dill.dumps(self.model, f)
pickle: TypeError: can't pickle instancemethod objects
joblib : PicklingError: Can't pickle <type 'instancemethod'>: it's not found as __builtin__.instancemethod
cPickle : TypeError: can't pickle instancemethod objects
dill : ValueError: pickle protocol must be <= 2
: type(r.model)
: sklearn.ensemble.forest.RandomForestClassifier
:with open('test.dill', 'wb') as f : dill.dump(r.model,f, protocol=2)
PicklingError: Can't pickle <class 'random_forest.RFWords'>: it's not the same object as random_forest.RFWords
random_forest.RFWords 是包含 RF 的类! 它如何访问 self.model 所在的类
嗯……我认为这是 IPython 的问题……因为现在我正在更仔细地测试它……有时它可以工作!!
可能是自动重载问题!!
Yep the moment I modify the source code save_model() stops working ..
最佳答案
使用 joblib 来 pickle 你训练好的模型:
from joblib import dump, load
from sklearn.ensemble import RandomForestClassifier
#load data
X, y = load_data(...)
#fit the model
estimator = RandomForestClassifier()
estimator.fit(X,y)
#pickle model to disk
dump(estimator, 'my_randomforest_model.joblib')
#loading saved model
estimator = load('my_randomforest_model.joblib')
estimator.predict(...)
更新:
根据这个错误,你必须使用更高的协议(protocol)进行 pickeling (>= 2):
dill : ValueError: pickle protocol must be <= 2
尝试使用更高的协议(protocol)进行转储,如下所示:
dump(estimator, 'my_randomforest_model.joblib', protocol=2)
关于python - 将随机森林模型保存到文件?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/57939025/