Human Friendliness of Classifiers: A Review

HADDELA, Prasanna, HIRSCH, Laurence, GAUDOIN, Jotham and BRUNSDON, Teresa (2020). Human Friendliness of Classifiers: A Review. In: Emerging Technologies in Data Mining and Information Security. Springer Advances in Intelligent Systems and Computing (AISC) . Springer.

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    Abstract

    During the past few decades Classifiers have become a heavily studied and well-researched area. Classifiers are often used in many modern applications as a core computing technique. However, it has been observed that many popular and highly accurate classifiers are lacking an important characteristic; that of human friendliness. This hinders the ability of end users to interpret and fine-tune the method of decision-making process as human friendliness allows for crucial decision making towards Applications. This paper presents, in term of classification (i) a taxonomy for human-friendliness (ii) comparisons with well-known classifiers as related to human friendliness, and (iii) discussion regarding recent developments and challenges in the field.

    Item Type: Book Section
    Additional Information: 2nd International Conference on Emerging Technologies in Data Mining and Information Security Kolkata, India Jul 2, 2020 - Jul 4, 2020
    SWORD Depositor: Symplectic Elements
    Depositing User: Symplectic Elements
    Date Deposited: 19 Jun 2020 09:21
    Last Modified: 19 Jun 2020 09:30
    URI: http://shura.shu.ac.uk/id/eprint/26480

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