python保存加载机器学习模型实例

尽量用pickle 不要用joblib,joblib好像后续不支持了。
import pickle
datafile2 =’…/data/model.xls’
datafile3=’…/data/model3.xls’ data2=pd.read_excel(datafile2)
print(“data2:”,data2)
data3=pd.read_excel(datafile3)
print(“data3:”,data3)
data = data2.append(data3)
print(“data:”,data)
data = data._values
print(“data_values:”,data) np.random.shuffle(data)
print(“after shuffle data:”,data)
p = 0.8
train=data[:int(len(data)*p),:]
test = data[int(len(data)*p):,:]
models_path = ‘…/models/’
print(“6. dt 分类”)
tree =DecisionTreeClassifier()
tree.fit(train[:,:3], train[:,3])
tree.predict(test[:,:3]) print(“predict:”,tree.predict(test[:,:3]))
print(“true :”,test[:,3])

dt_models_path = models_path +"tree.sav" 
pickle.dump(tree, open(dt_models_path, 'wb'))
 loaded_model = pickle.load(open(dt_models_path, 'rb'))  print("predict:",loaded_model.predict(test[:,:3]))