Empirical rapid and accurate prediction model for data mining tasks in cloud computing environments

Samaher Al-Janabi, Ahmed Patel, Hayder Fatlawi, Kenan Kalajdzic, Ibrahim Al Shourbaji

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    12 Citations (Scopus)

    Abstract

    With the arrival of big data and cloud computing as a computing concept, it is becoming ever more critical to efficiently choose the most optimum machine on which to execute a program, for example in the healthcare environment. This process of choice is also complicated by the fact that numerous machines are available as virtual machines. Hence, predicting the most optimum choice of machine based on a target application is a challenge. Prediction techniques consume large amount of computing resources when operating with multi-dimensional data that can cause long delays compounded by cross validation process in evaluating and choosing the most optimum prediction model. We propose a model of prediction techniques to predict and classify some of the health datasets to retrieve useful knowledge to illustrate how a data miner can choose a suitable machine especially in cloud environment with good accuracy in a timely manner. Our results show that the execution time has an inverse relation with the use of resources of a machine and the accuracy of prediction could be different from one machine to another using the same predicting technique and dataset.

    Original languageEnglish
    Title of host publication2014 International Congress on Technology, Communication and Knowledge, ICTCK 2014
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Print)9781479980215
    DOIs
    Publication statusPublished - 5 Feb 2015
    Event2014 International Congress on Technology, Communication and Knowledge, ICTCK 2014 - Mashhad
    Duration: 26 Nov 201427 Nov 2014

    Other

    Other2014 International Congress on Technology, Communication and Knowledge, ICTCK 2014
    CityMashhad
    Period26/11/1427/11/14

    Fingerprint

    Cloud computing
    Data mining
    Miners
    Health
    Prediction model
    Prediction

    Keywords

    • Cloud computing
    • Computer architectures
    • Data Miner
    • Healthcare Datasets
    • Predicting techniques

    ASJC Scopus subject areas

    • Computer Science(all)
    • Management of Technology and Innovation
    • Electrical and Electronic Engineering

    Cite this

    Al-Janabi, S., Patel, A., Fatlawi, H., Kalajdzic, K., & Al Shourbaji, I. (2015). Empirical rapid and accurate prediction model for data mining tasks in cloud computing environments. In 2014 International Congress on Technology, Communication and Knowledge, ICTCK 2014 [7033495] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICTCK.2014.7033495

    Empirical rapid and accurate prediction model for data mining tasks in cloud computing environments. / Al-Janabi, Samaher; Patel, Ahmed; Fatlawi, Hayder; Kalajdzic, Kenan; Al Shourbaji, Ibrahim.

    2014 International Congress on Technology, Communication and Knowledge, ICTCK 2014. Institute of Electrical and Electronics Engineers Inc., 2015. 7033495.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Al-Janabi, S, Patel, A, Fatlawi, H, Kalajdzic, K & Al Shourbaji, I 2015, Empirical rapid and accurate prediction model for data mining tasks in cloud computing environments. in 2014 International Congress on Technology, Communication and Knowledge, ICTCK 2014., 7033495, Institute of Electrical and Electronics Engineers Inc., 2014 International Congress on Technology, Communication and Knowledge, ICTCK 2014, Mashhad, 26/11/14. https://doi.org/10.1109/ICTCK.2014.7033495
    Al-Janabi S, Patel A, Fatlawi H, Kalajdzic K, Al Shourbaji I. Empirical rapid and accurate prediction model for data mining tasks in cloud computing environments. In 2014 International Congress on Technology, Communication and Knowledge, ICTCK 2014. Institute of Electrical and Electronics Engineers Inc. 2015. 7033495 https://doi.org/10.1109/ICTCK.2014.7033495
    Al-Janabi, Samaher ; Patel, Ahmed ; Fatlawi, Hayder ; Kalajdzic, Kenan ; Al Shourbaji, Ibrahim. / Empirical rapid and accurate prediction model for data mining tasks in cloud computing environments. 2014 International Congress on Technology, Communication and Knowledge, ICTCK 2014. Institute of Electrical and Electronics Engineers Inc., 2015.
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