Analytical Findings on Data Mining Algorithms

Abstract

The heart of issue pumps out several classification algorithms based on decision tree which is again one of the most prominent area in data mining .Data Mining constitutes discovery or extraction of various patterns or relationships by large data clusters. For this we can employ several strategies which can be based on statistics or artificial intelligence. Here we use classification as well as prediction methodologies which follows decision tree concept. Various classical approaches i.e. ID3 or C4.5 have been discussed and we discuss algorithms SLIQ ,SPRINT and FUDT which will help in avoidance of costly sorting by further discussing their characteristics, challenges they pose, advantages as well as disadvantages.