NARX model gives high accuracy but prediction of other data is too low
3 visualizzazioni (ultimi 30 giorni)
Mostra commenti meno recenti
I have created a NARX model using 1 external input and 1 target data set in time series. When I train the system with very long memory lengths for output, I got good accuracy for training but when I try to predict other data set from same system, prediction accuracy is very low.
then I combined 3 datasets sequencelly to train the network and then tried to predict each other seperately. let's say my dataset numbers are 1, 2 and 3, respectively. when I try to predict I got 79% accuracy for 3, 70% accuracy for 2 and 20% acccuracy for 1.
What is the reason of low accuracy for the dataset 1?
1 Commento
srinivasan jayalaxmi
il 16 Apr 2022
sir can any one help me out as how to find accuracy of NARX models
Risposte (1)
Aditya Patil
il 25 Set 2020
Generally, when you get good results when training, but poor results on test dataset, it means your model is overfitting. There are several techniques to improve accuracy in such situation. To get started, check out the Improve Shallow Neural Network Generalization and Avoid Overfitting documentation.
2 Commenti
Aditya Patil
il 20 Ott 2020
If you get low accuracy for training data, it means the model is not performing well.
Vedere anche
Categorie
Scopri di più su Modeling and Prediction with NARX and Time-Delay Networks in Help Center e File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!