دورية أكاديمية
A multi-feature hybrid classification data mining technique for human-emotion
| العنوان: | A multi-feature hybrid classification data mining technique for human-emotion |
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| المؤلفون: | Y. Wang, Y. M. Chu, A. Thaljaoui, Y. A. Khan, W. Chammam, S. Z. Abbas |
| المصدر: | BioData Mining, Vol 14, Iss 1, Pp 1-20 (2021) |
| بيانات النشر: | BMC, 2021. |
| سنة النشر: | 2021 |
| المجموعة: | LCC:Computer applications to medicine. Medical informatics LCC:Analysis |
| مصطلحات موضوعية: | Feature selection, Health care, Hybrid classification, Human-physic, Retrieval-ranking, Prediction, Computer applications to medicine. Medical informatics, R858-859.7, Analysis, QA299.6-433 |
| الوصف: | Abstract Background and objectives The ideal treatment of illnesses is the interest of every era. Data innovation in medical care has become extremely quick to analyze diverse diseases from the most recent twenty years. In such a finding, past and current information assume an essential job is utilizing and information mining strategies. We are inadequate in diagnosing the enthusiastic mental unsettling influence precisely in the beginning phases. In this manner, the underlying conclusion of misery expressively positions an extraordinary clinical and Scientific research issue. This work is dedicated to tackling the same issue utilizing the AI strategy. Individuals’ dependence on passionate stages has been successfully characterized into various gatherings in the data innovation climate. Methods A notable AI multi-include cross breed classifier is utilized to execute half and half order by having the passionate incitement as pessimistic or positive individuals. A troupe learning calculation helps to pick the more appropriate highlights from the accessible classes feeling information on online media to improve order. We split the Dataset into preparing and testing sets for the best proactive model. Results The execution assessment is applied to check the proposed framework through measurements of execution assessment. This exploration is done on the Class Labels MovieLens dataset. The exploratory outcomes show that the used group technique gives ideal order execution by picking the highlights’ greatest separation. The supposed results demonstrated the projected framework’s distinction, which originates from the picking-related highlights chosen by the incorporated learning calculation. Conclusion The proposed approach is utilized to precisely and successfully analyze the downturn in its beginning phase. It will assist in the recovery and action of discouraged individuals. We presume that the future strategy’s utilization is exceptionally appropriate in all data innovation-based E-medical services for discouraging incitement. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1756-0381 |
| Relation: | https://doaj.org/toc/1756-0381 |
| DOI: | 10.1186/s13040-021-00254-x |
| URL الوصول: | https://doaj.org/article/a75bd5424b904497bfbd4835e21601f0 |
| رقم الأكسشن: | edsdoj.75bd5424b904497bfbd4835e21601f0 |
| قاعدة البيانات: | Directory of Open Access Journals |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 17560381 |
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| DOI: | 10.1186/s13040-021-00254-x |