Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Feature selection based on the classifier models: Performance issues in the prediagnosis of lung cancer Subject The topic of the resource Artificial neural network; Classifier; Data mining; Feature selections; Lung cancer; Pre-diagnosis Description An account of the resource Dimensionality reduction is generally carried out to reduce the complexity of the computations in the large data set environment by removing redundant or de-pendent attributes. For the Lung cancer disease prediction, in the pre-diagnosis stage, symptoms and risk factors are the main information carriers. Large number of symptoms and risk attributes poses major challenge in the computation. Here in this study an attempt is made to compare the performance of the attribute selection models prior and after applying the classifier models. A total of 16 classifier models are preferred based on relevancy of the models with respect to the data types chosen, which are based on statistical, rule based, logic based and artificial neural network approaches. Feature set selection and ranking of attributes are done based on individual models. Based on the confusion matrix parameters the models prediction outcomes are found out in the supervisory training mode. The Confusion matrix of the models before and after dimensionality reduction is computed. Models are compared based on weighted Reader Operator Characteristics. Normalized weights are assigned based for the result of individual models and predictive model is developed. Predictive models performance is studied with target under supervised classifier model and it is observed that it is tallying with the expected outcome. 2005 - 2014 JATIT &amp; LLS. All rights reserved. Creator An entity primarily responsible for making the resource Balachandran K.; Anitha R. Source A related resource from which the described resource is derived Journal of Theoretical and Applied Information Technology, Vol-59, No. 3, pp. 549-555. Publisher An entity responsible for making the resource available Asian Research Publishing Network (ARPN) Date A point or period of time associated with an event in the lifecycle of the resource 2014-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-84893519101&amp;partnerID=40&amp;md5=05224267a85ff96196d7ae3c76bdaa3f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-84893519101&amp;partnerID=40&amp;md5=05224267a85ff96196d7ae3c76bdaa3f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 19928645 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Balachandran K., Computer Science and Engineering Department, Christ University, Bangalore, Karnataka, India; Anitha R., K.S.Rangasamy College of Technology, Tiruchengodu, Tamil Nadu, India