A case study of medical data classification using hybrid adboost kNn along with krill herd algorithm (KHA)

被引：1
作者：
Rafi D.M. [1 ]
Bharathi C.R. [1 ,3 ]
机构：
[1] Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology, Avadi, Chennai
[2] Vivekananda Institute of Engineering and Technology, JNTU University, Hyderabad
[3] Department of ECE, Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology, Avadi, Chennai, Tamil Nadu
来源：
Ingenierie des Systemes d'Information | 2019年 / 24卷 / 01期
关键词：
Accuracy; Case study investigation; Hybrid Adaboost k-nearest neighbor; Krill herd algorithm; Medical classification; Sensitivity; Specificity;
D O I：
10.18280/isi.240111
中图分类号：
学科分类号：
摘要：
This paper studies Medical classification challenging process methods using data ming, Hybrid Adboost KNN along with Krill Herd Algorithm (KHA) is applied to breast cancer medical data mining. Many death cases are happened due to breast cancer among ladies around the world, here tumor can identify as caused by disease. The data we study is collected from patients with breast cancer disease from hospitals. It is an ambiguous optimization problem and which is provide diagnosis aid effectiveness. It has 198 records of 34 attributes each. We use Krill Herd Algorithm to optimal features selection and Hybrid Adboost KNN is used to Classification. Case Study investigated the data mining methods and determine the Breast Cancer illness. The case study performance is evaluated in terms of accuracy, sensitivity and specificity. The Case Study will be implemented in Python software. © 2019 Lavoisier. All rights reserved.
引用
收藏
页码：77 / 81
页数：4
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