A Comparative Study of Meta Heuristic Model to Assess the Type of Breast Cancer Disease

Abstract

Breast cancer is the expansion of cancer from the breast tissue and a lump in the breast, a change in breast shape, dimpling of the skin, fluid coming from the nipple or a red scaly patch of skin. This disease is becoming a leading cause of death among women in the whole world; meanwhile, if it is recognized in the early stage and accurate diagnosis of this disease can ensure a long survival of women. Here, the knowledge base has been created using the concept of data mining to recognize the disease based on the early data. In this paper, data mining has been used to create the association rules and statistical, soft computing and evolution algorithms have been used to select optimal classifier based on earlier data. In this context, three types (training on the whole dataset and new tested data have been created, tenfold and 98% training and 2%tested data) of techniques have been used to estimate the disease type (named consequent item) based on the nine attributes (named antecedent item) of the breast cancer data set.

KEYWORDS:

• Ant colony optimization (ACO) harmony search, differential evolution algorithm
• Association rule
• Breast cancer
• Data mining
• Factor analysis
• Fuzzy logic
• Neural network
• Particle swarm intelligence (PSO)
• Principal component analysis

Additional information

Notes on contributors

Dharmpal Singh

Dharmpal Singh received his bachelors in computer science and engineering and masters of computer science and engineering from West Bengal University of Technology. He has over 13 years of experience in teaching and research. At present, he is with JIS College of Engineering, Kalyani,West Bengal, India as an associate professor. He obtained his PhD from the University of Kalyani. He has over 40 publications in national and international journals and conference proceedings. He is also the editorial board member of many reputed/refereed journals.

He is also the editorial board member of many reputed/referred journals.

J. Paul Choudhury

Jagannibas Paul Choudhury received his Bachelor of Electronics and Tele-Communication Engineering with Honors from Jadavpur University, Kolkata and Masters of Technology from Indian Institute of Technology, Kharagpur. He received his PhD (Engineering) from Jadavpur University. He has about 30 years experience in teaching, research, and administration. Now, he is with the Department of Information Technology, Future Engineering College, West Bengal, India as a Professor and the Head of Information Technology. He has about 110 publications in national and international journals and conference proceedings. His research fields are soft computing, data mining, clustering and classification, routing a computer network, etc. E-mail: [email protected]

Mallika De

Mallika De received her BSc in Physics from the Calcutta University in 1973 and MSc from the Jadavpur University in 1976. She received MTech in Computer Science from Indian Statistical Institute, Calcutta in 1985, and a PhD in Engineering from Jadavpur University in 1997. She is currently with JIS Group, India; she had 30 years of teaching experience in the University of Kalyani. Her research interests are parallel algorithms and architectures, fault-tolerant computing, image processing, and soft computing. She has authored of 10 refereed journal articles and 10 conference papers. E-mail: [email protected]