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Negative samples reduction in cross-company software defects prediction
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Outgoing claims: the papers this work cites, builds on, or argues with.
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SMOTE: Synthetic Minority Over-sampling Technique
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Cross-project defect prediction: a large scale experiment on data vs. domain vs. process
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Research on Cross-Company Defect Prediction Method to Improve Software Security
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Cross-Project Defect Prediction Based on Two-Phase Feature Importance Amplification
inferred← citeshttps://doi.org/10.1155/2022/6339684openalex-snapshot
Tsbagging: A Novel Cross-Project Software Defect Prediction Algorithm Based on Semisupervised Clustering
inferred← citeshttps://doi.org/10.1371/journal.pone.0247444openalex-snapshot
Attention based GRU-LSTM for software defect prediction
inferred← citeshttps://doi.org/10.1587/transinf.2016edl8238openalex-snapshot
Kernel CCA Based Transfer Learning for Software Defect Prediction
inferred← citeshttps://doi.org/10.17762/ijritcc.v11i6s.6933openalex-snapshot
Class Imbalance Reduction and Centroid based Relevant Project Selection for Cross Project Defect Prediction
inferred← citeshttps://doi.org/10.18293/seke2016-120openalex-snapshot
A Multi-Source TrAdaBoost Approach for Cross-Company Defect Prediction
inferred← citeshttps://doi.org/10.18293/seke2017-034openalex-snapshot
Is the Number of Faults Helpful for Cross-Company Defect Prediction?
inferred← citeshttps://doi.org/10.18293/seke2017-035openalex-snapshot
Using Class Imbalance Learning for Cross-Company Defect Prediction
inferred← citeshttps://doi.org/10.18293/seke2017-043openalex-snapshot
A Data Filtering Method Based on Agglomerative Clustering
inferred← citeshttps://doi.org/10.18293/seke2017-134openalex-snapshot
Combing Data Filter and Data Sampling for Cross-Company Defect Prediction: An Empricial Study
inferred← citeshttps://doi.org/10.18293/seke2019-070openalex-snapshot
Cross-Project Defect Prediction via Transferable Deep Learning-Generated and Handcrafted Features
inferred← citeshttps://doi.org/10.21203/rs.3.rs-2305042/v1openalex-snapshot
A Novel Approach for Software Defect Prediction using CNN and GRU Based on SMOTE Tomek Method
inferred← citeshttps://doi.org/10.21203/rs.3.rs-2305042/v2openalex-snapshot
A Novel Approach for Software Defect Prediction using CNN and GRU Based on SMOTE Tomek Method
inferred← citeshttps://doi.org/10.22266/ijies2021.0630.18openalex-snapshot
An Empirical Comparison of Resampling Ensemble Methods of Deep Learning Neural Networks for Cross-Project Software Defect Prediction
inferred← citeshttps://doi.org/10.22279/navus.2019.v9n4.p94-110.960openalex-snapshot
Inovação aberta: estratégia propulsora de valor em empresas de base tecnológica
inferred← citeshttps://doi.org/10.24251/hicss.2021.235openalex-snapshot
Machine Learning for Software Engineering: a Bibliometric Analysis from 2015 to 2019
inferred← citeshttps://doi.org/10.26599/tst.2020.9010040openalex-snapshot
A novel cross-project software defect prediction algorithm based on transfer learning
inferred← citeshttps://doi.org/10.3233/idt-210130openalex-snapshot
Local modeling approach for cross-project defect prediction
inferred← citeshttps://doi.org/10.3233/jifs-234415openalex-snapshot
RETRACTED: Hybridization of fuzzy rough feature selection with ANFIS and turbulent flow of water optimization for managing software defect prediction uncertainty
inferred← citeshttps://doi.org/10.32604/cmc.2020.08096openalex-snapshot
Within-project and cross-project software defect prediction based on improved transfer Naive Bayes algorithm
inferred← citeshttps://doi.org/10.32604/cmc.2023.045522openalex-snapshot
Software Defect Prediction Method Based on Stable Learning
inferred← citeshttps://doi.org/10.32628/cseit23902190openalex-snapshot
Predictive Analytics for Proactive Quality Assurance in Guidewire Cloud Implementations
inferred← citeshttps://doi.org/10.3390/app10228059openalex-snapshot
Credibility Based Imbalance Boosting Method for Software Defect Proneness Prediction
inferred← citeshttps://doi.org/10.3390/app9132660openalex-snapshot
Transfer Convolutional Neural Network for Cross-Project Defect Prediction
inferred← citeshttps://doi.org/10.3390/electronics13020456openalex-snapshot
Landmark-Based Domain Adaptation and Selective Pseudo-Labeling for Heterogeneous Defect Prediction
inferred← citeshttps://doi.org/10.3390/electronics14193930openalex-snapshot
Cognitive Bias Mitigation in Executive Decision-Making: A Data-Driven Approach Integrating Big Data Analytics, AI, and Explainable Systems
inferred← citeshttps://doi.org/10.3390/sym12030407openalex-snapshot
Class Imbalance Reduction (CIR): A Novel Approach to Software Defect Prediction in the Presence of Class Imbalance
inferred← citeshttps://doi.org/10.3934/mbe.2020054openalex-snapshot
Heterogeneous cross-project defect prediction with multiple source projects based on transfer learning
inferred← citeshttps://doi.org/10.48550/arxiv.1901.08429openalex-snapshot
Transfer-Learning Oriented Class Imbalance Learning for Cross-Project Defect Prediction
inferred← citeshttps://doi.org/10.48550/arxiv.1908.06560openalex-snapshot
Revisiting Heterogeneous Defect Prediction: How Far Are We?
inferred← citeshttps://doi.org/10.48550/arxiv.2002.03148openalex-snapshot
Understanding the Automated Parameter Optimization on Transfer Learning for CPDP: An Empirical Study
inferred← citeshttps://doi.org/10.48550/arxiv.2101.11749openalex-snapshot
An extensive empirical study of inconsistent labels in multi-version-project defect data sets
inferred← citeshttps://doi.org/10.51983/ajcst-2023.12.2.3763openalex-snapshot
A Comprehensive Hybrid Model for Language-Independent Defect Prediction in Microservices Architecture
inferred← citeshttps://doi.org/10.70675/04cad5d8zd06bz482dzbeb8z19b24a8aa3b5openalex-snapshot
A graph based end to end defect prediction framework.
inferred← citeshttps://doi.org/10.7867/1980-4431.2022v27n2p69-85openalex-snapshot
Open Innovation as a Strategy for Creating Value in Technology-based companies
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