Intelligent Crossover and Mutation Technique to Control Bloat for Breast Cancer Diagnosis

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{Khan:2015:CICN,

• author = "Arzoo Khan and Medhavi Chouhan",
• booktitle = "2015 International Conference on Computational Intelligence and Communication Networks (CICN)",
• title = "Intelligent Crossover and Mutation Technique to Control Bloat for Breast Cancer Diagnosis",
• year = "2015",
• pages = "387--391",
• abstract = "Breast cancer affects several people at present time. Diagnosis which determines whether the cancer is benign or malignant requires a lot of effort from doctors and physician. Early diagnosis may save many lives. Accurate classification plays an important role in medical diagnosis. Genetic programming is a machine learning algorithm which now days excelling in classification field. But Genetic programming generally face the problem of code bloating in which an increase in average tree size is found without a corresponding increase in fitness. In this paper we are proposing a new technique for solving the problem of bloat and for increasing classification accuracy. The technique is known as intelligent crossover and mutation technique. This technique is a combination of hill climbing and conventional method which will be applied on both crossover and mutation operator. To demonstrate this, we had taken WBC dataset from UCI repository which has 2 classes and 9 features and we have compared classification accuracy of our method with standard crossover and FEDS crossover. Our classification accuracy was 97.5percent for 50-50 training and testing methodology 95percent for 60-40, 99percent for 70-30, 99.5percent for 80-20 and 99.6percent for 10 fold cross validation technique. This shows our method can be used for medical diagnosis as it provides good results.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/CICN.2015.82",
• month = dec,
• notes = "Also known as \cite{7546120}",

}

Genetic Programming entries for Arzoo Khan Medhavi Chouhan

Citations