Thanks so much for the explanation. What is the variable "T" saved together with "Y" (training data output) and "TY"(testing data output)?. Sir, could you please give a link to download the error code you are using (Error1.m)? The one I wrote from your video is not displaying the error metrics like yours probably because you did not show the whole code while explaining it. Thanks in anticipation of your response and assistance.
Regarding Error code: you can find the code in the description of this video ruclips.net/video/wWiA2mBi9C4/видео.html "'T" refers to our training data input, if you see the previous video, in the first few lines you can find it there, i just place it for cross reference of the data.
Thanks so much for the clarification. I tried the code and after I normalised my data, the code performed very well with the training data but poorly with the test data. For example, the R2 for the training was 0.98 while it was 0.07 for the test set. What could be the problem?
@@olanrewajuogunsola9203 i think this might be the case of overtraining where the neural network tries to learn the pattern and causing it to make it perfect to the training model and there by not able to predict the testing set
i tried doing the same but correlation I am getting NaN in training and testing I checked the data and code multiple times but was unable to get the desired results. Please Help 🙏
Thanks so much for the explanation. What is the variable "T" saved together with "Y" (training data output) and "TY"(testing data output)?. Sir, could you please give a link to download the error code you are using (Error1.m)? The one I wrote from your video is not displaying the error metrics like yours probably because you did not show the whole code while explaining it. Thanks in anticipation of your response and assistance.
Regarding Error code: you can find the code in the description of this video
ruclips.net/video/wWiA2mBi9C4/видео.html
"'T" refers to our training data input, if you see the previous video, in the first few lines you can find it there, i just place it for cross reference of the data.
Thanks so much for the clarification. I tried the code and after I normalised my data, the code performed very well with the training data but poorly with the test data. For example, the R2 for the training was 0.98 while it was 0.07 for the test set. What could be the problem?
@@olanrewajuogunsola9203 i think this might be the case of overtraining where the neural network tries to learn the pattern and causing it to make it perfect to the training model and there by not able to predict the testing set
i tried doing the same but correlation I am getting NaN in training and testing I checked the data and code multiple times but was unable to get the desired results.
Please Help 🙏
sorry to hear that, but without knowing the data and code you are using i cannot help you with why you are getting NAN
Sir, I will contact you through mail.