On Rough Sets Non-deterministic Information Analysis and Machine Learning

Abstract

We have proposed the framework of Rough Sets Non-deterministic Information Analysis (RNIA) and are developing the execution environment. In this paper, we introduce the new execution environment in Python and show some examples. Then, we consider a framework of machine learning based on RNIA. In RNIA, we investigated certain rule generation from tables with missing values. We can recover a value for some missing values by using certain rules and sequentially revise this table to a table without missing values. We term this functionality Machine Learning by Rule Generation from incomplete information.