A survey on addressing high-class imbalance in big data
In a majority–minority classification problem, class imbalance in the dataset (s) can
dramatically skew the performance of classifiers, introducing a prediction bias for the …
dramatically skew the performance of classifiers, introducing a prediction bias for the …
Machine learning with big data: Challenges and approaches
The Big Data revolution promises to transform how we live, work, and think by enabling
process optimization, empowering insight discovery and improving decision making. The …
process optimization, empowering insight discovery and improving decision making. The …
Machine learning in polymer informatics
W Sha, Y Li, S Tang, J Tian, Y Zhao, Y Guo, W Zhang… - InfoMat, 2021 - Wiley Online Library
Polymers have been widely used in energy storage, construction, medicine, aerospace, and
so on. However, the complexity of chemical composition and morphology of polymers has …
so on. However, the complexity of chemical composition and morphology of polymers has …
[HTML][HTML] HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community
Recently, deep learning (DL) has emerged as a revolutionary and versatile tool transforming
industry applications and generating new and improved capabilities for scientific discovery …
industry applications and generating new and improved capabilities for scientific discovery …
Artificial intelligence to power the future of materials science and engineering
Artificial intelligence (AI) has received widespread attention over the last few decades due to
its potential to increase automation and accelerate productivity. In recent years, a large …
its potential to increase automation and accelerate productivity. In recent years, a large …
Convergence of gamification and machine learning: a systematic literature review
A Khakpour, R Colomo-Palacios - Technology, Knowledge and Learning, 2021 - Springer
Recent developments in human–computer interaction technologies raised the attention
towards gamification techniques, that can be defined as using game elements in a non …
towards gamification techniques, that can be defined as using game elements in a non …
[HTML][HTML] Qualitative case-based reasoning and learning
The development of autonomous agents that perform tasks with the same dexterity as
performed by humans is one of the challenges of artificial intelligence and robotics. This …
performed by humans is one of the challenges of artificial intelligence and robotics. This …
A literature survey on various aspect of class imbalance problem in data mining
S Goswami, AK Singh - Multimedia Tools and Applications, 2024 - Springer
Data has become much widely available in recent years. Since the past years, Learning
classifiers from unbalanced data is a crucial issue that comes up frequently in classification …
classifiers from unbalanced data is a crucial issue that comes up frequently in classification …
Investigating class rarity in big data
Abstract In Machine Learning, if one class has a significantly larger number of instances
(majority) than the other (minority), this condition is defined as class imbalance. With regard …
(majority) than the other (minority), this condition is defined as class imbalance. With regard …
An overview on the role of artificial intelligence in modern advancements of material science
Artificial intelligence (AI) has become a disruptive force in many industries over the past few
decades, and the subjects of material science and engineering are no exception. This …
decades, and the subjects of material science and engineering are no exception. This …