The balancing trick: Optimized sampling of imbalanced datasets—A brief survey of the recent State of the Art
This survey paper focuses on one of the current primary issues challenging data mining
researchers experimenting on real‐world datasets. The problem is that of imbalanced class …
researchers experimenting on real‐world datasets. The problem is that of imbalanced class …
Handling class-imbalance with KNN (neighbourhood) under-sampling for software defect prediction
S Goyal - Artificial Intelligence Review, 2022 - Springer
Abstract Software Defect Prediction (SDP) is highly crucial task in software development
process to forecast about which modules are more prone to errors and faults before the …
process to forecast about which modules are more prone to errors and faults before the …
Effective software defect prediction using support vector machines (SVMs)
S Goyal - International Journal of System Assurance Engineering …, 2022 - Springer
Software defect prediction (SDP) plays a key role in the timely delivery of good quality
software product. In the early development phases, it predicts the error-prone modules …
software product. In the early development phases, it predicts the error-prone modules …
Integrating Explainable AI with Federated Learning for Next-Generation IoT: A comprehensive review and prospective insights
The emergence of the Internet of Things (IoT) signifies a transformative wave of innovation,
establishing a network of devices designed to enrich everyday experiences. Developing …
establishing a network of devices designed to enrich everyday experiences. Developing …
Framework for improved sentiment analysis via random minority oversampling for user tweet review classification
Social networks such as twitter have emerged as social platforms that can impart a massive
knowledge base for people to share their unique ideas and perspectives on various topics …
knowledge base for people to share their unique ideas and perspectives on various topics …
Predicting the defects using stacked ensemble learner with filtered dataset
S Goyal - Automated Software Engineering, 2021 - Springer
Software defect prediction is a crucial software project management activity to enhance the
software quality. It aids the development team to forecast about which modules need extra …
software quality. It aids the development team to forecast about which modules need extra …
Enhancing sentiment analysis via random majority under-sampling with reduced time complexity for classifying tweet reviews
Twitter has become a unique platform for social interaction from people all around the world,
leading to an extensive amount of knowledge that can be used for various reasons. People …
leading to an extensive amount of knowledge that can be used for various reasons. People …
Multilabel over-sampling and under-sampling with class alignment for imbalanced multilabel text classification
AY Taha, S Tiun, AH Abd Rahman… - Journal of Information …, 2021 - e-journal.uum.edu.my
Simultaneous multiple labelling of documents, also known as multilabel text classification,
will not perform optimally if the class is highly imbalanced. Class imbalanced entails …
will not perform optimally if the class is highly imbalanced. Class imbalanced entails …
Heterogeneous Data-Aware Federated Learning for Intrusion Detection Systems via Meta-sampling in Artificial Intelligence of Things
Intrusion detection systems (IDSs) integrated with machine learning (ML) techniques have
proven to be effective defenses against the increasing cybersecurity attacks in the Artificial …
proven to be effective defenses against the increasing cybersecurity attacks in the Artificial …
A hybrid approach for optimizing software defect prediction using a grey wolf optimization and multilayer perceptron
Purpose Software defect prediction (SDP) is a critical aspect of software quality assurance,
aiming to identify and manage potential defects in software systems. In this paper, we have …
aiming to identify and manage potential defects in software systems. In this paper, we have …