HARDy: Handling Arbitrary Recognition of Data in Python

Abstract

HARDy is a Python-based package that helps evaluate differences in data through feature engineering coupled with kernel methods. The package provides an extension to machine learning by adding layers of feature transformation and representation. The workflow of the package is as follows: • Configuration: Sets attribute for user-defined transformations, machine learning hyperparameters or hyperparameter space • Handling: Imports pre-labelled data from .csv files and loads into the catalogue. Later the data will be split into training and testing sets • Arbitrage: Applies user defined numerical and visual transformations to all the data loaded. • Recognition: Machine Learning module that applies user defined hyperparameter search space for training and evaluation of model • Data-Reporting: Imports result of machine learning models and reports it into dataframes and plots