#!/users/dsc/bin/Python3
#-*-coding: UTF-8 -*-
from sklearn.neural_network import MLPClassifier #多层感知机分类器 MLP
from sklearn.linear_model import LogisticRegression #逻辑斯蒂回归分类器 LR
from sklearn.ensemble import RandomForestClassifier#随机森林分类器 RFC
from sklearn.tree import DecisionTreeClassifier#决策树 DTC

from sklearn.neural_network import  MLPRegressor #多层感知机回归模型 MLPR
from sklearn.linear_model import LinearRegression #线性回归模型 LRR
from sklearn.ensemble import RandomForestRegressor #随机森林回归 RFR
from sklearn.tree import DecisionTreeRegressor #决策树回归 DTR

import warnings
warnings.filterwarnings("ignore")#忽略警告

class Models():
    """_summary_
    模型集，包含：
    分类器
    1.多层感知机
    2.逻辑斯蒂回归
    3.随机森林
    4.决策树
    回归模型
    1.多层感知机
    2.逻辑斯蒂回归
    3.随机森林
    4.决策树
    """
    def __init__(self):
        cf1=MLPClassifier()
        cf2=LogisticRegression()
        cf3=RandomForestClassifier()
        cf4=DecisionTreeClassifier()
        rf1=MLPRegressor()
        rf2=LinearRegression()
        rf3=RandomForestRegressor()
        rf4=DecisionTreeRegressor()
        self.models={"MLP":cf1,"LR":cf2,"RFC":cf3,"DTC":cf4}
        self.regressors={"MLPR":rf1,"LRR":rf2,"RFR":rf3,"DTR":rf4}
    def model(self,model_name="MLP"):
        try:
            return self.models[model_name]
        except:
            return self.models["MLP"]
    def regressor(self,regressor_name="MLPR"):
        try:
            return self.regressors[regressor_name]
        except:
            return self.regressors["MLPR"]
models=Models()