A Kind of Inductive Learning Classification Algorithm Based on Statistics Rule

Author

Li, Yan ; Li, Fa-chao

Author_Institution

Coll. of Sci., Hebei Univ. of Sci. & Technol., Shijiazhuang

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

1308

Lastpage

1313

Abstract

Induce learning is one of the most important research areas on application of artificial intelligence. The classification algorithm is the core of the machine learning. The article advanced a kind of decision classification algorithm that is in view of attribute value statistical regularity, on the characteristic and insufficient of ID3, C4.5 algorithm. (In short of BS-CA) This algorithm takes the statistical regularity as foundation, and takes the multiplication as comprehensive tactics, simplifying the trimming and optimization processes of decision tree. The theory analysis and experiment shows that BS-CA possesses high accuracy, high classification speed, simple and high activity

Keywords

data mining; decision trees; learning by example; pattern classification; statistical analysis; C4.5 algorithm; ID3 algorithm; attribute value statistical regularity; decision classification algorithm; decision tree; inductive learning classification algorithm; machine learning; statistics rule; Classification algorithms; Classification tree analysis; Cybernetics; Decision trees; Economic forecasting; Educational institutions; Humans; Learning systems; Machine learning; Machine learning algorithms; Statistics; BS-CA; Classificication algorithm; Data mining; Induce learning; Statistical rule;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.258658

Filename

4028266