Paper Info
Title
Principles component analysis, fuzzy weighting pre-processing and artificial immune recognition system based diagnostic system for diagnosis of lung cancer
Abstract
Lung cancers are cancers that begin in the lungs. Other types of cancers may spread to the lungs from other organs. However, these are not lung cancers because they did not start in the lungs. It is evident that usage of machine learning methods in disease diagnosis has been increasing gradually. In this study, diagnosis of lung cancer, which is a very common and important disease, was conducted with such a machine learning system. In this study, we have detected on lung cancer using principles component analysis (PCA), fuzzy weighting pre-processing and artificial immune recognition system (AIRS). The approach system has three stages. First, dimension of lung cancer dataset that has 57 features is reduced to four features using principles component analysis. Second, a new weighting scheme based on fuzzy weighting pre-processing was utilized as a pre-processing step before the main classifier. Third, artificial immune recognition system was our used classifier. We took the lung cancer dataset used in our study from the UCI machine learning database. The obtained classification accuracy of our system was 100% and it was very promising with regard to the other classification applications in literature for this problem.
Year
DOI
Venue
2008
10.1016/j.eswa.2006.09.001
Expert Syst. Appl.
Keywords
Field
DocType
fuzzy weighting pre-processing,lung cancer,diagnostic system,artificial immune system,classification accuracy,airs,principles component analysis,medical diagnosis,artificial immune recognition system,approach system,lung cancer dataset,uci machine,pre-processing step,new weighting scheme,machine learning,principle component analysis
Lung cancer,Data mining,Weighting,Computer science,Artificial intelligence,Component analysis,Classifier (linguistics),Artificial immune system,Disease,Pattern recognition,Fuzzy logic,Machine learning,Medical diagnosis
Journal
Volume
Issue
ISSN
34
1
Expert Systems With Applications
Citations 
PageRank 
References 
37
1.52
4
Authors
2
Name
Order
Citations
PageRank
Kemal Polat1134897.38
Salih Güneş2126778.53