Integrating heterogeneous agriculture information using naive Bayes and FCA

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Authors: J.S. Kanchana and S. Sujatha
Date: June 30, 2016
From: Advances in Natural and Applied Sciences(Vol. 10, Issue 10 SE)
Publisher: American-Eurasian Network for Scientific Information
Document Type: Report
Length: 2,141 words
Lexile Measure: 1390L

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Abstract :

Data mining is an interdisciplinary subfield of computer science. It is the computational process of discovering patterns in large data sets. Naive Bayes is used in this paper which makes use of probability to classify real and discrete data. The Formal Concept Analysis is used in mapping the results of the Naive Bayes and the given data. In this paper, Naive Bayes algorithm is used to classify agricultural datasets and the results are mapped to farmer data using Formal Concept Analysis to provide recommendation for farmers. KEYWORDS:

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Gale Document Number: GALE|A465904544