DocumentCode :
2197713
Title :
IBLE Algorithm in Agricultural Disease Diagnosis
Author :
Jin HaiYue ; Song Kai
Author_Institution :
Sci. & Project Branch, Shenyang Inst. of Technol. Inf., Shenyang, China
fYear :
2010
fDate :
1-3 Nov. 2010
Firstpage :
401
Lastpage :
404
Abstract :
Although the ID3 algorithm holds the extremely important position in the data mining. But the ID3 algorithm existence cannot process the continual attribute, the computation information gain when the application the deviation in insufficiency and so on selection value many attributes. Therefore, one kind of advanced version decision-making tree algorithm IBLE was proposed that it mainly is uses in the information theory. The channel capacity concept to take chooses the important characteristic to the entity in the measure. Combines the rule with many characteristics the point to distinguish the example can effectively the correct distinction. This article applies this algorithm in the oral cavity disease diagnosis, the experimental result indicated this algorithm has the very strong recognition capability to agriculture case diagnosis to very good assistance diagnosis function.
Keywords :
agriculture; crops; data mining; decision making; diagnostic expert systems; IBLE algorithm; ID3 algorithm; agricultural disease diagnosis; computation information gain; data mining; decision-making tree algorithm; diagnostic expert system; field crop disease diagnosis; Data Mining; IBLE algorithm; diagnosing in agriculture disease;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Networks and Intelligent Systems (ICINIS), 2010 3rd International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-8548-2
Electronic_ISBN :
978-0-7695-4249-2
Type :
conf
DOI :
10.1109/ICINIS.2010.100
Filename :
5693570
Link To Document :
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