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.
|Name||Lecture Notes in Computer Science|
|Conference||International Joint Conference on Rough Sets|
|Period||29/06/20 → 3/07/20|
- rough sets
- statistical learning
- neighbourhood based rough sets