A novel approach for software defect prediction through hybridizing gradual relational association rules with artificial neural networks DL Miholca, G Czibula, IG Czibula Information Sciences 441, 152-170, 2018 | 128 | 2018 |
A novel concurrent relational association rule mining approach G Czibula, IG Czibula, DL Miholca, LM Crivei Expert Systems with Applications 125, 142-156, 2019 | 43 | 2019 |
An in-depth analysis of the software features’ impact on the performance of deep learning-based software defect predictors DL Miholca, VI Tomescu, G Czibula IEEE Access 10, 64801-64818, 2022 | 23 | 2022 |
An aggregated coupling measure for the analysis of object-oriented software systems IG Czibula, G Czibula, DL Miholca, Z Onet-Marian Journal of Systems and Software 148, 1-20, 2019 | 21 | 2019 |
COMET: A conceptual coupling based metrics suite for software defect prediction DL Miholca, G Czibula, V Tomescu Procedia Computer Science 176, 31-40, 2020 | 16 | 2020 |
Machine learning-based approaches for predicting stature from archaeological skeletal remains using long bone lengths G Czibula, VS Ionescu, DL Miholca, IG Mircea Journal of archaeological science 69, 85-99, 2016 | 16 | 2016 |
An improved approach to software defect prediction using a hybrid machine learning model DL Miholca 2018 20th International Symposium on Symbolic and Numeric Algorithms for …, 2018 | 15 | 2018 |
Software defect prediction using a hybrid model based on semantic features learned from the source code DL Miholca, G Czibula Knowledge Science, Engineering and Management: 12th International Conference …, 2019 | 14 | 2019 |
A new incremental relational association rules mining approach DL Miholca, G Czibula, LM Crivei Procedia Computer Science 126, 126-135, 2018 | 14 | 2018 |
Enhancing relational association rules with gradualness C Istvan-Gergely, C Gabriela, M Diana-Lucia 革新的コンピューティング・情報・制御に関する国際誌 13 (01), 289, 2017 | 14 | 2017 |
An analysis of aggregated coupling's suitability for software defect prediction DL Miholca, Z Oneţ-Marian 2020 22nd International Symposium on Symbolic and Numeric Algorithms for …, 2020 | 8 | 2020 |
Detecting depression from fMRI using relational association rules and artificial neural networks DL Miholca, A Onicaş 2017 13th IEEE International Conference on Intelligent Computer …, 2017 | 6 | 2017 |
Machine learning based approaches for sex identification in bioarchaeology DL Miholca, G Czibula, IG Mircea, IG Czibula 2016 18th International Symposium on Symbolic and Numeric Algorithms for …, 2016 | 5 | 2016 |
An unsupervised learning based conceptual coupling measure DL Miholca, G Czibula, Z Marian, IG Czibula 2017 19th International Symposium on Symbolic and Numeric Algorithms for …, 2017 | 4 | 2017 |
Machine-Learning-Based Approaches for Multi-Level Sentiment Analysis of Romanian Reviews A Briciu, AD Călin, DL Miholca, C Moroz-Dubenco, V Petrașcu, ... Mathematics 12 (3), 456, 2024 | 3 | 2024 |
An adaptive gradual relational association rules mining approach DL MIHOLCA Studia Universitatis Babeș-Bolyai Informatica, 94-110, 2018 | 3 | 2018 |
New Conceptual Cohesion Metrics: Assessment for Software Defect Prediction DL Miholca 2021 23rd International Symposium on Symbolic and Numeric Algorithms for …, 2021 | 2 | 2021 |
DynGRAR: A dynamic approach to mining gradual relational association rules DL Miholca, G Czibula Procedia Computer Science 159, 10-19, 2019 | 1 | 2019 |
Identifying Hidden Dependencies in Software Systems IG CZIBULA, G CZIBULA, DL MIHOLCA, Z MARIAN Studia Universitatis Babeș-Bolyai Informatica, 90-106, 2017 | 1 | 2017 |
Source-Code Embedding-Based Software Defect Prediction. DL Miholca, Z Onet-Marian ICSOFT, 185-196, 2023 | | 2023 |