Earticle

초록

영어

Data Mining is the process of extract information from a data set and transform it into an understandable structure. Classification is a data mining task, used to classify data among different predefined clusters. The paper proposes a new classifier utilizing MLP approach by maintaining the clusters based on similar feature. The improved MLP approach can handle noisy data, reduce complexity and increases the performance. This technique has been applied for automating medical diagnosis. This paper analyzes the lung CT-scan images for identifying and classifying them among the various lung diseases (i.e., bronchitis, emphysema, pleural effusion or normal) by emphasizing on the problematic area.

목차

Abstract
 1. Introduction
 2. Material and Method
 3. Proposed Approach
  3.1 Preprocessing
  3.2 Feature Extraction
  3.3 Feature Selection
  3.4 Classification
 4. Implementation & Results
 5. Conclusion
 References

키워드

저자

• Ramandeep Kaur [ M.Tech CSE Department, #CT Group of Engg. Mgt.&Tech, Jalandhar, India ]
• Prince Verma [ Assistant proff.,M.Tech, CSE Department, #CT Group of Engg., Mgmt., &Tech, , Jalandhar, India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605