A Comparative Study of Contemporary Learning Paradigms in Bug Report Priority Detection
<p dir="ltr">The increasing complexity of software development demands efficient automated bug report priority classification, and recent advancements in deep learning hold promise. This paper presents a comparative study of contemporary learning paradigms, including BERT, vector dat...
Saved in:
| Main Author: | Eyüp Halit Yilmaz (21400700) (author) |
|---|---|
| Other Authors: | İsmail Hakki Toroslu (21400703) (author), Ömer Köksal (21400706) (author) |
| Published: |
2024
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Optimizing malicious website prediction: An advanced XGBoost-based machine learning model
by: Sumaira Hussain (19259669)
Published: (2025) -
Active Learning Based Federated Learning for Waste and Natural Disaster Image Classification
by: Lulwa Ahmed (16869936)
Published: (2020) -
Evaluating machine learning technologies for food computing from a data set perspective
by: Nauman Ullah Gilal (17302714)
Published: (2023) -
Anomalies Detection in Software by Conceptual Learning From Normal Executions
by: Ahmad Qadeib Alban (16855206)
Published: (2020) -
An efficient approach for textual data classification using deep learning
by: Abdullah Alqahtani (7128143)
Published: (2022)