Closed 4 days ago.

My company produces embedded devices from which we collect a bunch of parameters (several hundred) in CSV files. Now I would like to find causal relationships between an important error parameter and all the other parameters. What I’ve done so far is training an SVM model with the important error parameter as the target and the remaining parameters as the features and then finding the features that contributed most to the target parameter. I am quite happy with the result as the most contributing labels actually make sense and the model achieves an accuracy above 90% on the test data.

My company produces embedded devices from which we collect a bunch of parameters (several hundred) in CSV files. Now I would like to find causal relationships between an important error parameter and all the other parameters. What I’ve done so far is training an SVM model with the important error parameter as the target and the remaining parameters as the features and then finding the features that contributed most to the target parameter. I am quite happy with the result as the most contributing labels actually make sense and the model achieves an accuracy above 90% on the test data.