Study of Meta, Naïve Bayes and Decision Tree based Classifiers

Abstract

Classification deals with the kind of data mining problem which are concerned with prediction. Its main task is to classify the data in order to make predictions about new data. In general Classification can be viewed as the action or process of classifying something. In Data mining one of the most common tasks is to build models for the prediction of the class of an object on the basis of its attributes. This paper has made a comparative study of various classification algorithms viz. Meta Classifiers, Naïve Bayes and Decision Tree Based Classifiers. An experiment has been set up using different kinds of classification algorithms to test their performance. Theoretical analysis and experimental results will show that ‘Classification via Regression’ method has correctly classify all the instances, minimum errors are produced by ‘Decision Tree based Classifiers’, whereas ‘Naïve Bayes’ has classified all the instances in minimum time span.

Authors and Affiliations

Abhinay Bishnoi, Deepak Sinwar

Keywords

Related Articles

Divisor Cordial Labeling Of Cycle Related Graphs

A divisor cordial labeling of a graph G is a bijection f from V (G) to {1, 2, . . . , |V (G)|} such that an edge uv is assigned the label 1 if f (u)| f (v) or f (v)| f (u) and the label 0 otherwise, then the number of e...

slugNeed of Quality Research for improving Higher Technical Education

The number of private colleges has increased tremendously in the last 15 years due to shortage of government aided colleges and due to the large demand of engineers and technical personals in private and public secto...

slugPerformance Improvement of Ad-Hoc Networks Using Multi-Interface Multi-Channel Mac and Routing Protocols

IEEE 802.11 MAC standard allocates single channel, single interface to each node in the case of wireless ad-hoc networks, as a default behavior of this protocol. The same feature of single channel, single interface per...

A Review of Water Absorption, Porosity and Sorptivity of Cement Mortar made with metakaolin and flyash partially replaced in cement cured in seawater

In this present study the effects of flyash, metakaolin and their combinations has been evaluated for optimal level of replacement as blending component in cement. The results showed that the water absorption, porosity...

Advanced Microwave Active & Passive Remote Sensing Application and Its Utilization

Microwave sensing circumscribes both active and passive forms of remote sensing. Long wavelengths, match up to the visible and infrared. Its radiation can penetrate through haze, cloud cover and dust. Longer wavelengths...

Download PDF file
  • EP ID EP18561
  • DOI -
  • Views 431
  • Downloads 17

How To Cite

Abhinay Bishnoi, Deepak Sinwar (2014). Study of Meta, Naïve Bayes and Decision Tree based Classifiers. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2(8), -. https://europub.co.uk/articles/-A-18561