pre_y_train.append( [func(x, regr.coef_[0], regr.coef_[1], regr.intercept_)]) pre_y_train = np.array(pre_y_train) pre_y_test = [] for x in data.test.X: pre_y_test.append( [func(x, regr.coef_[0], regr.coef_[1], regr.intercept_)]) pre_y_test = np.array(pre_y_test) print(train_num, end='\t\t') for a in input_dim: if (a == 0): print("冠幅cw ", end='') elif (a == 1): print("面积CA ", end='') elif (a == 2): print("树高CH ", end='') print('\t', end="") #print(err.calc_rmse(data.train.Y,data.train.predict_Y),end='\t') print(err.calc_rmse(data.train.Y, pre_y_train), end='\t') print(err.calc_rmse(data.test.Y, pre_y_test), end='\t') print(err.calc_err_rate(data.test.Y, pre_y_test), end='\t\t') #print(,end="") print([regr.coef_, regr.intercept_], end="") print()
pre_y_train = [] for x in data.train.mean_and_std_X: pre_y_train.append(func(x, popt[0], popt[1], popt[2])) pre_y_train = np.array(pre_y_train) data.train.re_mean_and_std(pre_y_train) pre_y_test = [] for x in data.test.mean_and_std_X: pre_y_test.append(func(x, popt[0], popt[1], popt[2])) pre_y_test = np.array(pre_y_test) data.test.re_mean_and_std(pre_y_test) print(train_num, end='\t\t') for a in input_dim: if (a == 0): print("冠幅 cw", end='\t\t') elif (a == 1): print("面积 CA", end='\t\t') elif (a == 2): print("树高 CH", end='\t\t') print(err.calc_rmse(data.train.Y, data.train.predict_Y), end='\t') print(err.calc_rmse(data.test.Y, data.test.predict_Y), end='\t') print(err.calc_err_rate(data.test.Y, data.test.predict_Y), end='\t') print(popt, end="") print()
for x in data.train.X: pre_y_train.append(func(x,popt[0],popt[1])) pre_y_train=np.array(pre_y_train) pre_y_test=[] for x in data.test.X: pre_y_test.append(func(x,popt[0],popt[1])) pre_y_test=np.array(pre_y_test) print(train_num,end='\t\t') for a in input_dim: if(a==0): print("冠幅 cw",end='\t\t') elif(a==1): print("面积 CA",end='\t\t') elif(a==2): print("树高 CH",end='\t\t') #print(err.calc_rmse(data.train.Y,data.train.predict_Y),end='\t') print(err.calc_rmse(data.train.Y,pre_y_train),end='\t') print(err.calc_rmse(data.test.Y,pre_y_test),end='\t') print(err.calc_err_rate(data.test.Y,pre_y_test),end='\t') print(popt,end="") print()
pre_y_train=np.array(pre_y_train) data.train.re_mean_and_std(pre_y_train) pre_y_test=[] for x in data.test.mean_and_std_X: pre_y_test.append(func(x,popt[0],popt[1],popt[2])) pre_y_test=np.array(pre_y_test) data.test.re_mean_and_std(pre_y_test) print(train_num,end='\t\t') for a in input_dim: if(a==0): print("冠幅 cw",end='\t\t') elif(a==1): print("面积 CA",end='\t\t') elif(a==2): print("树高 CH",end='\t\t') print(err.calc_rmse(data.train.Y,data.train.predict_Y),end='\t') print(err.calc_rmse(data.test.Y,data.test.predict_Y),end='\t') print(err.calc_err_rate(data.test.Y,data.test.predict_Y),end='\t') print(popt,end="") print()