Active k-labelsets ensemble for multi-label classification
The random k-labelsets ensemble (RAkEL) is a multi-label learning strategy that integrates
many single-label learning models. Each single-label model is constructed using a label …
many single-label learning models. Each single-label model is constructed using a label …
A low-rank learning-based multi-label security solution for industry 5.0 consumers using machine learning classifiers
The need for networking in smart industries known as Industry 5.0 has grown critical, and it
is especially important for the security and privacy of the applications. To counter threats to …
is especially important for the security and privacy of the applications. To counter threats to …
Materials representation and transfer learning for multi-property prediction
S Kong, D Guevarra, CP Gomes… - Applied Physics …, 2021 - pubs.aip.org
The adoption of machine learning in materials science has rapidly transformed materials
property prediction. Hurdles limiting full capitalization of recent advancements in machine …
property prediction. Hurdles limiting full capitalization of recent advancements in machine …
Multi-label classification based ensemble learning for human activity recognition in smart home
In recent times with advancements in wireless sensor technologies, human activity
recognition in smart home environments have gained significant interest amongst the …
recognition in smart home environments have gained significant interest amongst the …
A machine learning-based recommender system for improving students learning experiences
Outcome-based education (OBE) is a well-proven teaching strategy based upon a
predefined set of expected outcomes. The components of OBE are Program Educational …
predefined set of expected outcomes. The components of OBE are Program Educational …
Aspect based multi-labeling using SVM based ensembler
K Aurangzeb, N Ayub, M Alhussein - IEEE Access, 2021 - ieeexplore.ieee.org
Sentiment analysis is one of the most prominent sub-areas of research in Natural Language
Processing (NLP), where it is important to consider implicit or explicit emotions conveyed by …
Processing (NLP), where it is important to consider implicit or explicit emotions conveyed by …
Multimodal Analysis of Unbalanced Dermatological Data for Skin Cancer Recognition
PA Lyakhov, UA Lyakhova, DI Kalita - IEEE Access, 2023 - ieeexplore.ieee.org
To date, skin cancer is the most commonly diagnosed form of cancer in humans and is one
of the leading causes of death in cancer patients. AI technologies can match and exceed …
of the leading causes of death in cancer patients. AI technologies can match and exceed …
Clustered Automated Machine Learning (CAML) model for clinical coding multi-label classification
A Mustafa, M Rahimi Azghadi - International Journal of Machine Learning …, 2024 - Springer
Clinical coding is a time-consuming task that involves manually identifying and classifying
patients' diseases. This task becomes even more challenging when classifying across …
patients' diseases. This task becomes even more challenging when classifying across …
Predicting and characterising persuasion strategies in misinformation content over social media based on the multi-label classification approach
Persuasion aims at affecting the audience's attitude and behaviour through a series of
messages containing persuasion strategies. In the context of misinformation spread …
messages containing persuasion strategies. In the context of misinformation spread …
Multiple protein subcellular locations prediction based on deep convolutional neural networks with self-attention mechanism
H Cong, H Liu, Y Cao, Y Chen, C Liang - … Sciences: Computational Life …, 2022 - Springer
As an important research field in bioinformatics, protein subcellular location prediction is
critical to reveal the protein functions and provide insightful information for disease …
critical to reveal the protein functions and provide insightful information for disease …