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A Comparative Study on Decision Tree and Random Forest Using R Tool
IJARCCE - Computer and Communication Engineering
2015
IJARCCE
IJARCCE - Computer and Communication Engineering
Data mining is a process of extracting valuable information from large set databases. Classification a supervised technique is assigning data samples to target classes. This paper discusses two classification algorithms namely decision trees and Random forest.. Decision trees are powerful and popular tools for classification and prediction. Decision trees represent rules, which can be understood by humans and used in knowledge system such as database. Random forest includes construction of
doi:10.17148/ijarcce.2015.4142
fatcat:p4sdxrtksrh6beh6bdqk5vlvhy