How can i unnormalize the forecasted system load outputs in Neural Networks in Matlab
2 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
I normalised and unnormalised training and test data as mentioned below and hwo can i unnormalise the forecased output to the scale of test data ?
% normalising training and test data
[pn,ps] = mapminmax(input_train);
[tn,ts] = mapminmax(target_train);
[pn1,ps1] = mapminmax(input_test);
[tn1,ts1] = mapminmax(target_test);
forecastedoutput=net(pn1);
an = sim(net,pn);
a = mapminmax('reverse',an,ts);
0 comentarios
Respuestas (1)
Srivardhan Gadila
el 31 de Oct. de 2020
It is recommended to normalize the entire dataset first and then split it for training and testing so that the normalization would be consistent.
Or use the same normalization settings which are used for training data to normalize the testing data:
% normalising training data
[pn,ps] = mapminmax(input_train);
[tn,ts] = mapminmax(target_train);
% normalize test data with settings used for normalizing the training data
pn1 = mapminmax('apply',input_test,ps);
tn1 = mapminmax('apply',target_test,ts);
an = sim(net,pn1);
a = mapminmax('reverse',an,ts);
0 comentarios
Ver también
Categorías
Más información sobre Sequence and Numeric Feature Data Workflows en Help Center y File Exchange.
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!