Comparative Analysis of Decision Tree Classification Algorithms

dc.contributor.authorKarmachrya, Shikha
dc.date.accessioned2023-02-23T06:51:43Z
dc.date.available2023-02-23T06:51:43Z
dc.date.issued2014
dc.description.abstractIn our daily life there is lots of records, phone call records, salary records, homework records, assignment record, personal details record, sales record, song, videos and so on. These all records kept in a table are called data; we have lots of data in different field. Whenever there is data we can have lots of information, patterns, meaning etc. Data mining applications has got rich focus due to its significance of classification algorithms. The comparison of classification algorithm is a complex and it is an open problem. First, the notion of the performance can be defined in many ways: accuracy, speed, cost, reliability, etc. Second, an appropriate tool is necessary to quantify this performance. Third, a consistent method must be selected to compare with the measured values. The selection of the best classification algorithm for a given dataset is a very widespread problem. In this sense it requires to make several methodological choices. So this research focused in the analysis of decision tree classification algorithm in different datasets of multiple attributes and multiple instances. Where analysis was done among five decision tree algorithms (BFTree, J48, Random Tree, REP Tree and Simple Cart).J 48 was able to classify 82.16% of the data correctly which was best among all in comparison to results of evaluation metrics (Accuracy, Precision, Recall and F-Measure) and Simple Cart was able to build decision tree with small tree size of 17.24 (averaged value). Keywords: BF Tree,CART, Data Mining, Decision Tree, J48,Random Tree, REP Tree.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14540/15402
dc.language.isoen_USen_US
dc.publisherDepartment of Computer Science and Information Technologyen_US
dc.subjectComparative analysisen_US
dc.subjectRandom treeen_US
dc.subjectDecision treeen_US
dc.titleComparative Analysis of Decision Tree Classification Algorithmsen_US
dc.typeThesisen_US
local.academic.levelMastersen_US
local.institute.titleCentral Department of Computer Science and Information Technologyen_US
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