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Applying Naive Bayes Data Mining Technique for Classification of Agricultural Land Soils


P.Bhargavi, S.Jyothi


Vol. 9  No. 8  pp. 117-122


The advances in computing and information storage have provided vast amounts of data. The challenge has been to extract knowledge from this raw data that has lead to new methods and techniques such as data mining that can bridge the knowledge gap. This research aimed to assess these new data mining techniques and apply them to a soil science database to establish if meaningful relationships can be found. A large data set of Soil database is extracted from the Department of Soil Sciences and Agricultural Chemistry, S V Agricultural College, Tirupati, The database contains measurements of soil profile data from various locations of Chandragiri Mandal, Chittoor District. The research establishes whether Soils are Classified Using various data mining techniques. In addition, comparison was made between Naive bayes classification and analyse the most effective technique. The outcome of the research may have many benefits, t o agriculture, soil management and environmental.


Naive bayes, soil profiles, Bayesian Statistics, Soil Database, Classification