Determining the best-fit programmers using Bayes' theorem and artificial neural network
A data mining-based technique is proposed for the selection and employment of the best-fit programmers to meet the needs of software companies. The proposed technique incorporates Bayes' theorem and artificial neural network (ANN). The datasets used were from two software companies (Company 1 a...
Saved in:
Main Authors: | Prathan, Sorada, Ow, Siew Hock |
---|---|
Format: | Article |
Published: |
Wiley
2020
|
Subjects: | |
Online Access: | http://eprints.um.edu.my/36524/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Determining the best-FIT programmers using prognostic attributes / Sorada Prathan
by: Sorada , Prathan
Published: (2018) -
Bayes' theorem for multi-bearing faults diagnosis.
by: Yeo, Siang Chuan, et al.
Published: (2023) -
Stories of the Unplanned Impact of Mathematics: Bayes’ Theorem meets Cyberspace
by: Oxley, A.
Published: (2013) -
Hybrid artificial neural network-naive bayes classifier for solving imbalanced dataset problems
by: Adam, Asrul
Published: (2012) -
Artificial neural network — Naïve bayes fusion for solving classification problem of imbalanced dataset
by: Adam, A., et al.
Published: (2011)