Expert System for Land Suitability Evaluation using Data mining‘s Classification Techniques: a Comparative Study
C.Parthiban, M.Balakrishnan "Expert System for Land Suitability Evaluation using Data mining‘s Classification Techniques: a Comparative Study". International Journal of Computer Trends and Technology (IJCTT) V33(2):87-92, March 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
Data mining involves the extraction of
implicit, “interesting” information from a
database. Classification is an important Data
mining’s “machine learning” technique which is
used to predict data instances from dataset. It
involves the order wise analysis of large amount of
information sets. Data mining applications are
used in various areas such as health care,
insurance, medicines, Agriculture, banking and soil
management. In soil region the Data mining mainly
used to classify the soil and predicting the land
suitability for the crop and fertilizer
recommendation. The purpose of this study is to
predict the land suitability for the crop using
classification algorithms namely Naive Bayes and
J48. This work focused on find out the best
classification algorithm based on accuracy
measure, performance measure, error rate and
execution time using the soil dataset. From the
experimental result using WEKA tool it is observed
that the performance of the J48 is better than the
Naive Bayes algorithm.
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Keywords
WEKA, Data Mining, Naïve Bayes,
J48, Soil Dataset, Classification Algorithm.