Self-adaptive attribute weighting for Naive Bayes classification

•Self-adaptive attribute weighting for Naive Bayes classification.•Using Artificial Immune Systems (AIS) for attribute weighting.•Seamlessly integrating learning objective and AIS affinity function for attribute weighting.•Experiments on 42 real-world datasets demonstrating superb performance gain....

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Expert systems with applications Jg. 42; H. 3; S. 1487 - 1502
Hauptverfasser:	Wu, Jia, Pan, Shirui, Zhu, Xingquan, Cai, Zhihua, Zhang, Peng, Zhang, Chengqi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier Ltd 15.02.2015 Elsevier
Schlagworte:	Accuracy Algorithmics. Computability. Computer arithmetics Applied sciences Artificial Immune Systems Artificial intelligence Attribute weighting Bayesian analysis Classification Computer science; control theory; systems Data processing. List processing. Character string processing Evolutionary computing Exact sciences and technology Learning Learning and adaptive systems Machine learning Memory organisation. Data processing Naive Bayes Pattern recognition. Digital image processing. Computational geometry Self-adaptive Software Theoretical computing Weighting Self-adaptive Evolutionary computing Naive Bayes Artificial Immune Systems Attribute weighting Initialization Artificial life Image processing Multicriteria analysis Evolutionary algorithm Adaptability Conditional probability Probabilistic reasoning Immunity Modeling Adaptive method Data specification Efficiency Selection criterion Probability learning Immune system Bayes estimation Local search Computer vision Data analysis Probabilistic approach Image databank Independence Text Multidimensional database Supervised learning Learning (artificial intelligence) Artificial intelligence Image classification
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!