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The Impact of Rule Evaluation Metrics as a Conflict Resolution Strategy

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New Trends in Information and Communications Technology Applications (NTICT 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1183))

Abstract

It is crucial for each rule induced via machine learning algorithm is to be associated with a numerical value(s) which can reflect its properties like accuracy, coverage, likelihood. The accumulation of these properties is the so-called evaluation metrics. These metrics are important for both rule induction systems (for stopping rules generation) and rule classification systems (for solving rules conflict). This paper describes the most important of both statistical and empirical rule evaluation metrics. Thereafter, the paper presents an approach that utilizes and shows the impact of these metrics as a rule conflict resolution strategy during classification tasks when combining two heterogeneous classifiers (Naïve Bayes (henceforth, NB) and decision tree J48). To accomplish this goal, authors have extracted rule-set from J48 and presented a new method for rule construction from NB. Experiments have been conducted on (WBC, Vote, and Diabetes) datasets. The experimental results show that different evaluation metrics have a different impact on the classification accuracy when used as a conflict resolution strategy.

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Notes

  1. 1.

    According to Filter Technique, features are selected in isolation from data mining algorithms (i.e. before classification model is run) using some techniques to select the most appropriate features [22].

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Author information

Authors and Affiliations

  1. Ministry of Higher Education, Baghdad, Iraq

    Nabeel H. Al-A’araji

  2. Collage of Business Informatics, University of Information Technology and Communications, Baghdad, Iraq

    Safaa O. Al-Mamory

  3. Collage of Information Technology, University of Babylon, Hillah, Iraq

    Ali H. Al-Shakarchi

Authors
  1. Nabeel H. Al-A’araji
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  2. Safaa O. Al-Mamory
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  3. Ali H. Al-Shakarchi
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Corresponding authors

Correspondence to Nabeel H. Al-A’araji , Safaa O. Al-Mamory or Ali H. Al-Shakarchi .

Editor information

Editors and Affiliations

  1. University of Information Technology and Communications, Baghdad, Iraq

    Abbas M. Al-Bakry

  2. University of Information Technology and Communications, Baghdad, Iraq

    Safaa O. Al-Mamory

  3. University of Information Technology and Communications, Baghdad, Iraq

    Mouayad A. Sahib

  4. University of Information Technology and Communications, Baghdad, Iraq

    Haitham S. Hasan

  5. Open University of Tanzania, Dar es Salaam, Tanzania

    George S. Oreku

  6. University of Information Technology and Communications, Baghdad, Iraq

    Thaker M. Nayl

  7. University of Information Technology and Communications, Baghdad, Iraq

    Jaafar A. Al-Dhaibani

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Al-A’araji, N.H., Al-Mamory, S.O., Al-Shakarchi, A.H. (2020). The Impact of Rule Evaluation Metrics as a Conflict Resolution Strategy. In: Al-Bakry, A., et al. New Trends in Information and Communications Technology Applications. NTICT 2020. Communications in Computer and Information Science, vol 1183. Springer, Cham. https://doi.org/10.1007/978-3-030-55340-1_8

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  • DOI: https://doi.org/10.1007/978-3-030-55340-1_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-55339-5

  • Online ISBN: 978-3-030-55340-1

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