Models.py 文件源码

def First_Model_SVR(Scaled_Input_Data, Output_Data):
    T0 = time.time()
    n = len(Scaled_Input_Data)
    Grid_Dict = {"C": [1e-2, 1e-1,1e0, 1e1, 1e2],"gamma": np.logspace(-4, 2, 6)}
    svr_Tuned = GridSearchCV(SVR(kernel='rbf', gamma=0.1, tol = 0.005), cv=5,param_grid=Grid_Dict, scoring="mean_absolute_error")
    svr_Tuned.fit(Scaled_Input_Data, Output_Data)
    SVR_MSE = SVR(kernel='rbf', C=svr_Tuned.best_params_['C'], gamma=svr_Tuned.best_params_['gamma'], tol = 0.01)
    SVR_Time = time.time() - T0
    print('The computational time of Radial based Support Vector Regression for ', n, ' examples is: ', SVR_Time)
    MSEs_SVR = cross_validation.cross_val_score(SVR_MSE, Scaled_Input_Data, Output_Data, cv=cross_validation.LeaveOneOut(n), scoring="mean_absolute_error")
    MeanMSE_SVR = np.mean(list(MSEs_SVR))
    print('The average MSE of Radial based Support Vector Regression for ', n, ' examples is: ', (-1*MeanMSE_SVR))
    return(MeanMSE_SVR, svr_Tuned)