Distinction between mechine learning models and process models

aryans14

I am having a confusion about machine learning models and process models. What I know is machine learning models are for prediction but on contrary process models are the ones that are the actual models based upon the actual data.

I need further clear cut distinction here. We perform feature selection in machine learning to predict variables that result in best model accuracy. What equal analogy exist in process mining. I mean let say I want to divide the event log data for clustering the traces of an event log. Can I use machine learning features extraction and feature selection techniques or I have to develop custom feature extraction and selection techniques that leads to selection of best features. What should be the criteria to evaluate features selection for best clustering?

aryans14

No response so far from any group members