モデルの保存と取り出し

モデルの保存と取り出し

scikit-learn

import pickle
with open('model.pickle', mode='wb') as fp:
    pickle.dump(clf, fp)

import pickle
with open('model.pickle', mode='rb') as fp:
    clf = pickle.load(fp)
clf.predict(df)

XGBoost

import xgboost as xgb
import pickle

# save the model
model = xgb.XGBClassifier(max_depth=4)
model.fit(X_train, y_train)

pickle.dump(model, open("xgb_model.pickle", "wb"))

# load model from file
loaded_model = pickle.load(open("xgb_model.pickle", "rb"))

y_pred_proba = loaded_model.predict_proba(X_test)
y_pred = loaded_model.predict(X_test)

chainer

# save model
from chainer import serializers

model = L.Classifier(myDNN(100, 500, 10))
serializers.save_npz("mymodel.npz", model) 

# load model
from chainer import serializers

model = L.Classifier(myDNN(100, 500, 10)) # saveした時と同じ構成
serializers.load_npz("mymodel.npz", model)

※注意
セーブした時と、同じ構成でmodelを作ってあげないとロードできない。