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Open Access
Article
Publication date: 26 August 2021

Israa Mahmood and Hasanen Abdullah

Traditional classification algorithms always have an incorrect prediction. As the misclassification rate increases, the usefulness of the learning model decreases. This paper…

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Abstract

Purpose

Traditional classification algorithms always have an incorrect prediction. As the misclassification rate increases, the usefulness of the learning model decreases. This paper presents the development of a wisdom framework that reduces the error rate to less than 3% without human intervention.

Design/methodology/approach

The proposed WisdomModel consists of four stages: build a classifier, isolate the misclassified instances, construct an automated knowledge base for the misclassified instances and rectify incorrect prediction. This approach will identify misclassified instances by comparing them against the knowledge base. If an instance is close to a rule in the knowledge base by a certain threshold, then this instance is considered misclassified.

Findings

The authors have evaluated the WisdomModel using different measures such as accuracy, recall, precision, f-measure, receiver operating characteristics (ROC) curve, area under the curve (AUC) and error rate with various data sets to prove its ability to generalize without human involvement. The results of the proposed model minimize the number of misclassified instances by at least 70% and increase the accuracy of the model minimally by 7%.

Originality/value

This research focuses on defining wisdom in practical applications. Despite of the development in information system, there is still no framework or algorithm that can be used to extract wisdom from data. This research will build a general wisdom framework that can be used in any domain to reach wisdom.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

Keywords

Book part
Publication date: 15 October 2018

Thorsten Botz-Bornstein

The author launched an online survey at a private English-speaking university in Kuwait to evaluate the status, value and importance of Japanese and Korean popular cultures in…

Abstract

The author launched an online survey at a private English-speaking university in Kuwait to evaluate the status, value and importance of Japanese and Korean popular cultures in Kuwait. East-Asian culture is a subculture that is very widespread in the region because of Internet use and the influence of English-speaking education. The survey shows that this subculture can be understood as an alternative culture because it tends to contain a dissimulated critique of traditional Kuwaiti culture. Many students approach Japanese and Korean cultural products because they are in search of a coherent lifestyle founded on certain ethics. The Japanese–Kuwaiti cultural transfer implies a double resistance towards the local culture and towards American culture. The resulting marginalization is therefore two-fold. Resistance towards Western culture is here not based, as is often assumed in Arab contexts, on cultural closure and conservatism, but rather on the willingness to engage with an alien culture. This creates a paradoxical pattern of resistance to both the East and the West through adherence to another Eastern culture. The phenomenon can be understood in terms of globalisation as well as of anti-globalisation.

Details

Subcultures, Bodies and Spaces: Essays on Alternativity and Marginalization
Type: Book
ISBN: 978-1-78756-512-8

Keywords

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