<?xml version="1.0" encoding="utf-8"?>
<Journal>
<Journal-Info>
<name>International Journal of Pharma and Bio Sciences</name>
<website>ijpbs.net</website>
<email>editorijpbs@rediffmail.com (or) editorofijpbs@yahoo.com (or) prasmol@rediffmail.com</email>
</Journal-Info>
<article>
<article-id pub-id-type='other'>10.22376/ijpbs.2019.10.1.p1-12</article-id>
<issue_number>Volume 4 Issue 4</issue_number>
<issue_period>2013 (October - December)</issue_period>
<title>CONSRUCTION OF META CLASSIFIERS FOR APPLE SCAB INFECTIONS </title>
<abstract>Impact of infections on fruits like apple is very high if it is not predicted and acted upon. Classification as one of the major data mining methodologies can be applied effectively for this purpose. The objective of this paper is to check the learning algorithms for classification such examples based on selected dataset for apple scab . The main intention in this context is to deal with available data set for high accuracy. For this purpose Ada Boost, Bagging, Logit Boost models are built using an open source mining Weka under supervised learning algorithms. It is necessary to reduce the error before constructing the final models and thus the varying the parameters and number of iterations for training is carried out.</abstract>
<authors>A.KUMARAVEL AND D.UDHAYAKUMARAPANDIAN</authors>
<keywords>Data mining, Classification, Meta classifiers, Base Classifiers, Apple Scab, Search Methods Bagging Boosting.</keywords>
<pages>1207-1213</pages>
</article>
</Journal>
