A STUDY : SOIL CLASSIFICATION USING DATA MINING TECHNIQUES

Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/1459

Full metadata record

DC Field	Value	Language
dc.contributor.author	T S, Anushya Devi	-
dc.date.accessioned	2020-09-14T06:43:59Z	-
dc.date.available	2020-09-14T06:43:59Z	-
dc.date.issued	2018-04	-
dc.identifier.issn	2395-2539	-
dc.identifier.uri	https://www.google.com/search?client=firefox-b-d&ei=_kSPXLbgLMfgz7sPhoKg8Ag&q	-
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/1459	-
dc.description.abstract	Indian economy is depending on agriculture. Data mining is an important tool for extracting hidden information from large and varied data. The techniques of data mining are extremely popular in the area of agriculture. Data Mining Techniques such as K-Means, K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN) and Support Vector Machines (SVM), Bi-clustering, Naïve Bayes Classifier, J48, JRip are very recent applications of Data Mining techniques in agriculture field. In this paper focus on Data mining techniques used to compare and analyze the soil data.	en_US
dc.language.iso	en	en_US
dc.publisher	International Journal of Computer Engineering and Applied Sciences	en_US
dc.subject	Agriculture	en_US
dc.subject	Data mining	en_US
dc.subject	k-means	en_US
dc.subject	bi-clustering	en_US
dc.subject	k nearest neighbor	en_US
dc.subject	Artificial Neural Network	en_US
dc.subject	Support Vector Machine	en_US
dc.subject	Naïve Bayesian Classifier	en_US
dc.subject	J48	en_US
dc.subject	JRip	en_US
dc.title	A STUDY : SOIL CLASSIFICATION USING DATA MINING TECHNIQUES	en_US
dc.type	Article	en_US
Appears in Collections:	International Journals

Files in This Item:

File	Description	Size	Format
A STUDY SOIL CLASSIFICATION USING DATA MINING TECHNIQUES.docx		10.38 kB	Microsoft Word XML	View/Open