What is the relationship between examples dataset and model?

[cudmore]

You describe how to create a number of dataset including: arrhythmia, inter-patient beat, intra-patient beat, and Rpeak.

You then describe how to create a beat detection model in a few steps like: data preparation, training, inference, and results.

As a user, I do not understand the connection between me running the code to create these 4 different dataset(s) and then the model code with an additional 4 steps.

Can you create a new page(s) in your documentation to explain this to me?

When I run the dataset code, is that used in the model code? If so, how?

[devnums]

The documentation now includes a page that explains all the examples. https://pyheartlib.readthedocs.io/en/latest/examples/examples.html

Both examples 3 and 4 show how the RpeakData class can be used to create datasets. However, in Example 4, there are steps to use the datasets for training a deep learning model. In both examples, the RpeakData class is used, but the output datasets are different. Example 4 demonstrates a specific use case for it.