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()