@inproceedings{c5886bb0ac5f4f6685d25a344190b390,
title = "Rough sets meet statistics - a new view on rough set reasoning about numerical data",
abstract = "In this paper, we present a new view on how the concept of rough sets may be interpreted in terms of statistics and used for reasoning about numerical data. We show that under specific assumptions, neighborhood based rough approximations may be seen as statistical estimations of certain and possible events. We propose a way of choosing the optimal neighborhood size inspired by statistical theory. We also discuss possible directions for future research on the integration of rough sets and statistics.",
keywords = "rough sets, statistical learning, neighbourhood based rough sets",
author = "Marko Palangeti{\'c} and Chris Cornelis and Salvatore Greco and Roman S{\l}owi{\'n}ski",
year = "2020",
month = jul,
day = "7",
doi = "10.1007/978-3-030-52705-1_6",
language = "English",
isbn = "978-3-030-52704-4",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "78--92",
editor = "R. Bello and D. Miao and R. Falcon and M. Nakata and A. Rosete and D. Ciucci",
booktitle = "Rough Sets: IJCRS 2020",
note = "International Joint Conference on Rough Sets ; Conference date: 29-06-2020 Through 03-07-2020",
}