Paper Info
Title
Probabilistic Binary Classification With Use Of 2d Cellular Automata
Abstract
In this paper are presented wide known classification methods modified from almost deterministic into probabilistic forms. The rule for the classification problem designed by Fawcett, known as n4_V1_nonstable is modified into two proposed forms partially (n4_V1_nonstable_PP) and fully probabilistic (n4_V1_nonstable_FP). The effectiveness of classifications of these three methods is analysed and compared. The classification methods are used as the rules in the two-dimensional three-state cellular automaton with the von Neumann and Moore neighbourhood. Preliminary experiments show that probabilistic modification of Fawcett's method can give better results in the process of reconstruction (classification) than the original algorithm.
Year
DOI
Venue
2016
10.1007/978-3-319-44365-2_45
CELLULAR AUTOMATA, ACRI 2016
Keywords
Field
DocType
Cellular automaton, Binary classification, Reconstruction, Nondeterministic methods
Cellular automaton,Discrete mathematics,Binary classification,Computer science,Probabilistic logic,Stochastic cellular automaton,Von Neumann architecture
Conference
Volume
ISSN
Citations 
9863
0302-9743
1
PageRank 
References 
Authors
0.46
5
1
Name
Order
Citations
PageRank
Miroslaw Szaban1348.81