Volume 12 Number 12 (Dec. 2017)
Home > Archive > 2017 > Volume 12 Number 12 (Dec. 2017) >
JSW 2017 Vol.12(12): 923-933 ISSN: 1796-217X
doi: 10.17706/jsw.12.12.923-933

Comparative Analysis of Meta Learning Algorithms for Liver Disease Detection

Maruf Pasha1*, Meherwar Fatima2
1Department of Information Technology, Bahauddin Zakariya University, Pakistan.
2Department of Computer Science and Information Technology, Women University, Pakistan.

Abstract—Various kinds of pressure and unbalanced eating behaviors, along with alcohol inhalation and on-going toxic gases, absorption of tainted nutrients, unnecessary intake of cured food and ingestion of drug, enables patients to increase year by year from liver disease. For this purpose, the type of data mining algorithms can help medical doctors to diagnose patients in hospital. This paper analyzes meta learning algorithms to classify the Indian liver patient dataset. The Data set is attained from UCI repository that contains 583 instances. Adaboost, logitboost, Bagging and Grading meta learning algorithms are applied to this data set. These algorithms are compared on the basis of Correct Classification, Incorrect Classification and Time to build model. Grading is the best algorithm among these meta learning algorithms as it provides highest Correct Classification rate and minimum rate of incorrect classification. Execution time for Grading is less than Adaboost, Logitboost and Bagging. Key role is played by Grading algorithm in shaping enhanced classification accuracy (Correct Classification Rate) of a data set.

Index Terms—Disease diagnostic, data mining, machine learning, meta learning.


Cite: Maruf Pasha, Meherwar Fatima, "Comparative Analysis of Meta Learning Algorithms for Liver Disease Detection," Journal of Software vol. 12, no. 12, pp. 923-933, 2017.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
  • Apr 26, 2021 News!

    Vol 14, No 4- Vol 14, No 12 has been indexed by IET-(Inspec)     [Click]

  • Jun 22, 2020 News!

    Papers published in JSW Vol 14, No 1- Vol 15 No 4 have been indexed by DBLP     [Click]

  • Sep 13, 2021 News!

    The papers published in Vol 16, No 6 have all received dois from Crossref    [Click]

  • Jan 28, 2021 News!

    [CFP] 2021 the annual meeting of JSW Editorial Board, ICCSM 2021, will be held in Rome, Italy, July 21-23, 2021   [Click]

  • Sep 13, 2021 News!

    Vol 16, No 6 has been published with online version     [Click]