# Data processing and CFFS algorithm

Norveg and Szeged datasets are applying different settings and parameters, due to different scale and distributions, those are noted in codes comments
-"misc" folder: Contain the original feature names and the new ones which were developed for easyer interpretation and display.
-"raw_values"folder: 
    filter_3axis.py: banpass filtering and basic preprocessing steps.
    The two csv folder contain the useable parts of the datasets.
-"zcm" folder: Previously developed and updated codes for data processing and feature engineering, the present study applyed for PIM data, of coruse.
-"pyacty_features" folder: Implementation for the pyActigraphy python library functions, to calculate the standard actigraphy features.
-"cliques" folder: Correlation graph and click searching algorithm.
-"ML"folder: The implemented machine learning algorithms with exact parameters and SHAP calculation functions.
    
