عنوان انگلیسی مقاله:
Generalized fuzzy logic based performance prediction in data mining
ترجمه فارسی عنوان مقاله:
پیش بینی عملکرد مبتنی بر منطق فازی تعمیم یافته در داده کاوی
Sciencedirect - Elsevier - Materials Today: Proceedings, Corrected proof: doi:10:1016/j:matpr:2020:08:626
In recent days, the single and multiple economies depend upon the human capital to build a valuable service. The individual employee level is important to process and maintain the whole organization. Consequently, performance management is needed at each employee level and the business level to implement a system in order to measure the employee performance and provide growth based on the performance. In data mining applications, the knowledge discovery of interest in Human Resources Management (HRM) is applicable. To extract the knowledge significant data mining classification techniques were used. The scope of this work compares the predictive analyzing of theC4.5 algorithm, Naive Bayes and Fuzzy logics are made by comparing its accuracy. This paper proposed a framework to help human resource to monitor the employee performance. The exact accuracy of the proposed framework found to be more efficient in terms of the accurately predicting the outcome of the employee.© 2020 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Advances in Materials Research – 2019.
Keywords: Employee performance prediction | Data mining | Naive Bayes | Fuzzy logics | Decision tree | C4.5algorithm