Comparative Analysis of Decision Three Methods For The Prediction Of Paddy Productivity

dc.contributor.authorBhatt, Chaturbhuj
dc.date.accessioned2022-05-08T10:17:30Z
dc.date.available2022-05-08T10:17:30Z
dc.date.issued2019-11
dc.description.abstractData mining applications has got rich focus due to its significance of classification algorithms. The agricultural data is difficult to study. The challenge from a research perspective is to identify the key attributes that determine paddy performance across different farming situations such as geographic location, soil types, and seasonal conditions. This study aims to survey on the two different decision tree algorithms with primary data set collected in Kanchanpur district and to implement as well as assist by comparing J48 and Simple Cart decision tree methods to predict the production of paddy. From the result analysis it was seen that Simple Cart was able to classify 80.198% of the data correctly which was better than J48 in comparison to results of evaluation metrics (Accuracy, Precision, Recall and F-Measure). In a nut shell, the experiment result showed that J48 has got smaller tree size than Simple Cart but Simple Cart has got 1.9802% better accuracy than J48 for the prediction of paddy productivity.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14540/10189
dc.language.isoen_USen_US
dc.publisherDepartment of Computer Scienceen_US
dc.subjectClassificationen_US
dc.subjectPaddy Productivityen_US
dc.subjectCarten_US
dc.subjectData Miningen_US
dc.titleComparative Analysis of Decision Three Methods For The Prediction Of Paddy Productivityen_US
dc.typeThesisen_US
local.academic.levelMastersen_US
local.institute.titleCentral Department of Computer Science and Information Technologyen_US
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