@inproceedings{0df840efa1a246a3a0ccce57ae26e91b,
title = "Selecting representative prototypes for prediction the oxygen activity in electric arc furnace",
abstract = "Selecting a set of representative prototypes in prediction systems enable us to generate prototype based rules (P-Rules), which constitute a very powerful means of providing domain experts with knowledge about the data and the process depicted by the data. P-rules has already proved very useful in classification tasks. This paper investigates application of P-rules to regression problems. The problem of our concern is prediction of oxygen activity in an electric arc furnace during steel scrap melting. For that purpose we use a new algorithm for determining prototype positions, which is based on conditional clustering. Also a comparison between the new algorithm and the classical clustering-based methods for prototype extraction is described.",
keywords = "Context Dependent Clustering, Electric Arc Furnace, Industrial Application, Instance Selection, Nearest Neighbor, Regression",
author = "Marcin Blachnik and Miros{\l}aw Kordos and Tadeusz Wieczorek and S{\l}awomir Golak",
year = "2012",
doi = "10.1007/978-3-642-29350-4\_64",
language = "English",
isbn = "9783642293498",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
number = "PART 2",
pages = "539--547",
booktitle = "Artificial Intelligence and Soft Computing - 11th International Conference, ICAISC 2012, Proceedings",
address = "Germany",
edition = "PART 2",
note = "11th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2012 ; Conference date: 29-04-2012 Through 03-05-2012",
}