Progamme: Banking and Finance

Permanent URI for this collectionhttp://itsupport.cu.edu.ng:4000/handle/123456789/28787

Here you will find works strictly related to Banking and Finance.

News

https://bfn.covenantuniversity.edu.ng/

Browse

Has files: YesSubject: search.filters.subject.machine learning

Search Results

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Unsupervised learning analysis of European working condition
    (Cogent Business & Management VOL. 11, NO. 1,, 2024) Adesina, Olumide S.; Adedotun, Adedayo F.; Alayande, Semiu A.; Efe-Imafidon, Emmanuel O.; Adesina, Tolulope F.; Okagbue, Hillary I.; Onayemi, Oluwakemi O.
    Workers require good working conditions to enhance their job performance, in this study, we conducted a survey of European working conditions in 2022 and compared the results with that of 2016 using an unsupervised learning approach for exploratory data analysis and determining the relationships. Hence, the Principal Component Analysis (PCA ) was adopted. The analyses were in two parts for both the 2016 and 2022 surveys. Following the PCA , the first part shows that European workers are mostly characterized by cheerfulness and good spirits. The second part reveals that European workers are best characterized by enthusiasm in their work. Test statistics showed that the European working condition for the two periods does not differ significantly. The working conditions in Europe have not been altered in the space of six years. This study recommends that the working condition in Europe should be improved so that employers would continue to give their best.
  • No Thumbnail Available
    Item
    Knowledge, Attitude, and Perception of Health and Non-Healthcare Workers Towards COVID-19 Vaccination: Machine Learning Approach
    (2022) Adesina, Tolulope
    There have been concerns globally as to whether taking COVID-19 vaccination is harmful or not. In this study, we conducted an online survey to measure the knowledge and attitude of people, first about COVID-19, and second about COVID-19 vaccination—various analyses such as descriptive statistics, logistic regression, and support vector regression with k-fold cross-validation. The support vector machine and tuned support vector machine suggest a better fit based on cross-validation error. The results show that immigration requirements significantly explain why an individual would accept the COVID-19 vaccine. This study suggests that people in authority should look into people's concerns regarding taking the COVID-19 vaccine and address them accordingly. The study aims to draw the attention of the people to the concern that surrounds taking COVID-19 vaccination and explored various statistical techniques to draw inference.