A Survey on Decision Tree Algorithm for Classification

  Patel Brijain R,  Kaushik K Rana

Data mining is the process of discovering or extracting new patterns from large data sets involving methods from statistics and artificial intelligence. Classification and prediction are the techniques used to make out important data classes and predict probable trend .The Decision Tree is an important classification method in data mining classification. It is commonly used in marketing, surveillance, fraud detection, scientific discovery. As the classical algorithm of the decision tree ID3, C4.5, C5.0 algorithms have the merits of high classifying speed, strong learning ability and simple construction. However, these algorithms are also unsatisfactory in practical application. When using it to classify, there does exists the problem of inclining to choose attribute which have more values, and overlooking attributes which have less values. This paper provides focus on the various algorithms of Decision tree their characteristic, challenges, advantage and disadvantage.

Keywords- Decision tree algorithms, ID3, C4.5, C5.0, classification techniques

Unique Identification Number - IJEDR1401001
Page Number(s) - 1-5
Pubished in - Volume 2 | Issue 1 | March 2014
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Patel Brijain R,  Kaushik K Rana,   "A Survey on Decision Tree Algorithm for Classification", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.2, Issue 1, pp.1-5, March 2014, Available at :http://www.ijedr.org/papers/IJEDR1401001.pdf