Hi Youngwoo,
I understand you're encountering an error related to the output dimensions of your network. Given that your input data is a sequence, the network is treating this as a sequence-to-sequence model, which requires the output to also be a sequence with a feature dimension of 5. Here, "feature dimension" means that each output should be an array with a length of 5.
The error arises because the "classificationLayer" at the end of your network is designed to predict one of the 5 classes, whereas your model expects a vector of length 5 for its output. If your goal is to perform classification on your data, the "numClasses" property is relevant. However, if you're solving a sequence prediction problem, you'll need to format your data so that the output is a sequence of vectors, each with a length of 5.
For more information about the following topics, refer to the below documentation:
- Classification Layer : https://www.mathworks.com/help/deeplearning/ug/create-simple-deep-learning-network-for-classification.html#:~:text=fully%20connected%20layer.-,Classification%20Layer,-The%20final%20layer
- Sequence-to-sequence classification: https://www.mathworks.com/help/deeplearning/ug/sequence-to-sequence-classification-using-deep-learning.html
I hope it helps.
