Struktura obiektu

Autor:

Woźniak, Michał ; Krawczyk, Bartosz

Współtwórca:

Cordón, Oskar - ed. ; Kazienko, Przemysław - ed.

Tytuł:

Combined classifier based on feature space partitioning

Podtytuł:

Hybrid and Ensemble Methods in Machine Learning

Tytuł publikacji grupowej:

AMCS, Volume 22 (2012)

Temat i słowa kluczowe:

pattern recognition ; combined classifier ; multiple classifier system ; clustering and selection algorithm ; evolutionary algorithms

Abstract:

This paper presents a significant modification to the AdaSS (Adaptive Splitting and Selection) algorithm, which was developed several years ago. The method is based on the simultaneous partitioning of the feature space and an assignment of a compound classifier to each of the subsets. ; The original version of the algorithm uses a classifier committee and a majority voting rule to arrive at a decision. The proposed modification replaces the fairly simple fusion method with a combined classifier, which makes a decision based on a weighted combination of the discriminant functions of the individual classifiers selected for the committee. ; The weights mentioned above are dependent not only on the classifier identifier, but also on the class number. The proposed approach is based on the results of previous works, where it was proven that such a combined classifier method could achieve significantly better results than simple voting systems. ; The proposed modification was evaluated through computer experiments, carried out on diverse benchmark datasets. The results are very promising in that they show that, for most of the datasets, the proposed method outperforms similar techniques based on the clustering and selection approach.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2012

Typ zasobu:

artykuł

DOI:

10.2478/v10006-012-0063-0

Strony:

855-866

Źródło:

AMCS, Volume 22, Number 4 (2012) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego