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All Journal Journal of Applied Science, Engineering, Technology, and Education JINAV: Journal of Information and Visualization
Elgimati, Yousef
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Other

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Weighted Bagging in Decision Trees: Data Mining Elgimati, Yousef
JINAV: Journal of Information and Visualization Vol. 1 No. 1 (2020)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav149

Abstract

The main focus of this paper is on the use of resampling techniques to construct predictive models from data and the goal is to identify the best possible model which can produce better predications. Bagging or Bootstrap aggregating is a general method for improving the performance of given learning algorithm by using a majority vote to combine multiple classifier outputs derived from a single classifier on a bootstrap resample version of a training set. A bootstrap sample is generated by a random sample with replacement from the original training set. Inspired by the idea of bagging, we present an improved method based on a distance function in decision trees, called modified bagging (or weighted Bagging) in this study. The experimental results show that modified bagging is superior to the usual majority vote. These results are confirmed by both real data and artificial data sets with random noise. The Modified bagged classifier performs significantly better than usual bagging on various tree levels for all sample sizes. An interesting observation is that the weighted bagging performs somewhat better than usual bagging with sumps.
Effect of a COVID-19 on Social, Psychological, Economic and Health Conditions in Libya Elgimati, Yousef; Alrasheed, Ahmed; Mohamed Bashir, Abdalla
Journal of Applied Science, Engineering, Technology, and Education Vol. 3 No. 2 (2021)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (928.321 KB) | DOI: 10.35877/454RI.asci136

Abstract

The purpose of this paper was to measure the effect of a COVID-19 on social, psychological, economic, and health conditions in Libyan society. This study was undertaken through a questionnaire survey using the Google Form survey questionnaires in order to collect the data. A random sampling method was used from 1st June to 15th July 2020by obtaining greater insight into the issue. A result of this study revealed that the COVID-19 had a different effect on four dimensions (social, psychological economic, and health conditions). The findings of the study indicate that there is a small positive effect on social, middle, and above middle positive effects on psychological and economic respectively and high positive effect on health conditions with various percentages in Libyan society. This has been one of the first academic studies on the COVID-19 on social, psychological, economic, and health conditions addressed the Libyan society. Arguably, many of the areas covered in this study warrant more specific and in-depth investigation. The researchers hope that this paper will be beneficial to both Libyan people and the government in improving and developing the social aspects to avoid spreading COVID-19 in the future.
Co-Authors Alrasheed, Ahmed Mohamed Bashir, Abdalla