Question

我要使用以下代码选择型号。

import numpy as np
import pandas as pd
from math import log
from sklearn import model_selection
from sklearn.model_selection import train_test_split as split
from sklearn.metrics import accuracy_score as accuracy
import xgboost as xgb

dataframe_training = pd.read_csv("train.csv")
train_tag=dataframe_training['tags']
train_dummies_tags= train_tag.str.get_dummies(",")
dataframe_training=dataframe_training.filter(items=['review_ratio','log_date_difference','log_price'])
x_train=pd.concat([dataframe_training,train_dummies_tags], axis=1, sort=False)

y_train=dataframe_training.filter(items=['playtime_forever'])

Xtrain, Xtest, Ytrain, Ytest = split(x_train,y_train, test_size=0.25, random_state=7)



 from sklearn.ensemble import *
 AllRegressorModel = [xgb.XGBRegressor,AdaBoostRegressor,BaggingRegressor,ExtraTreesRegressor,GradientBoostingRegressor,RandomForestRegressor]

def Model_Selection_By_Cross_Valid():
        ThisRound_SelectedModel = None,
        ThisRound_SelectedModel_Name = None,
        ThisRound_SelectedModel_Score = None,
        for temp_select_model_name in AllRegressorModel:
            kfold = model_selection.KFold(n_splits=10, random_state=7),
            print (kfold),
            temp_model= temp_select_model_name(),
            temp_model.fit(Xtrain, Ytrain.ravel()),
            results = model_selection.cross_val_score(temp_model, X_train, Y_train.ravel(), cv=kfold, scoring='neg_mean_squared_error'),
        print(temp_select_model_name,results.mean()),
        if (ThisRound_SelectedModel == None) or (abs(results.mean()) < ThisRound_SelectedModel_Score):
            ThisRound_SelectedModel = temp_model,
            ThisRound_SelectedModel_Name = temp_select_model_name,
            ThisRound_SelectedModel_Score = abs(results.mean()),
        print ("This round Model Name: ", temp_model,"MSE Score: ",abs(results.mean())),
        print ("This Model Feature Importance",temp_model.feature_importances_),
        print("This Model Do No Have Feature Importance......"),
        print ("<----------------------------------->"),
        print ("Selected Model Name:", ThisRound_SelectedModel, "MSE Score:",ThisRound_SelectedModel_Score),
        return {"ModelName": ThisRound_SelectedModel_Name,"Model": ThisRound_SelectedModel}

运行程序时，

SelectedModel = Model_Selection_By_Cross_Valid()

AttributeError：“元组”对象没有属性“ fit”。

我该如何解决问题？

非常感谢您。

AttributeError：“元组”对象在选择模型时没有属性

0 个答案: