Advisory system for adapting a single machine problem to a distributed solution
| dc.contributor.author | Orynbekova Kamila | |
| dc.date.accessioned | 2024-09-17T11:28:22Z | |
| dc.date.available | 2024-09-17T11:28:22Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | General characteristics of the work. The work encompasses developing an advisory system to recommend solutions for single-machine problems adaptable to distributed systems, mainly focusing on implementation within the MapReduce platform. Methodologically, an experiment evaluated learning effectiveness, while extensive data collection informed model development. Predictive models, including Naive Bayes and Logistic Regression, were optimized and integrated into a recommendation system validated through rigorous evaluation. The aim of the research is to develop an advisory system that recommends single-machine problem solutions that adapt to distributed systems and are suitable for implementation on the MapReduce platform. | |
| dc.identifier.citation | Advisory system for adapting a single machine problem to a distributed solution / Orynbekova Kamila / 6D070400 – Computing Systems and Software / Kaskelen, 2024 | |
| dc.identifier.uri | https://repository.sdu.edu.kz/handle/123456789/1533 | |
| dc.language.iso | en | |
| dc.publisher | SDU University | |
| dc.subject | MapReduce | |
| dc.subject | Naive Bayes | |
| dc.subject | data | |
| dc.subject | Apache Spark | |
| dc.subject | PHD dissertation | |
| dc.title | Advisory system for adapting a single machine problem to a distributed solution |