Machine learning in precision agriculture: a survey on trends, applications and evaluations over two decades
Precision agriculture represents the new age of conventional agriculture. This is made
possible by the advancement of various modern technologies such as the internet of things …
possible by the advancement of various modern technologies such as the internet of things …
Data preprocessing for heart disease classification: A systematic literature review
H Benhar, A Idri, JL Fernández-Alemán - Computer Methods and Programs …, 2020 - Elsevier
Context Early detection of heart disease is an important challenge since 17.3 million people
yearly lose their lives due to heart diseases. Besides, any error in diagnosis of cardiac …
yearly lose their lives due to heart diseases. Besides, any error in diagnosis of cardiac …
Consensus clustering‐based undersampling approach to imbalanced learning
A Onan - Scientific Programming, 2019 - Wiley Online Library
Class imbalance is an important problem, encountered in machine learning applications,
where one class (named as, the minority class) has extremely small number of instances …
where one class (named as, the minority class) has extremely small number of instances …
Machine learning for financial risk management: a survey
Financial risk management avoids losses and maximizes profits, and hence is vital to most
businesses. As the task relies heavily on information-driven decision making, machine …
businesses. As the task relies heavily on information-driven decision making, machine …
A novel XGBoost extension for credit scoring class-imbalanced data combining a generalized extreme value link and a modified focal loss function
J Mushava, M Murray - Expert Systems with Applications, 2022 - Elsevier
There is often a significant class imbalance in credit scoring datasets, mainly in portfolios of
secured loans such as mortgage loans. A class imbalance occurs when the number of non …
secured loans such as mortgage loans. A class imbalance occurs when the number of non …
Cost-sensitive BERT for generalisable sentence classification with imbalanced data
The automatic identification of propaganda has gained significance in recent years due to
technological and social changes in the way news is generated and consumed. That this …
technological and social changes in the way news is generated and consumed. That this …
An empirical comparison on state-of-the-art multi-class imbalance learning algorithms and a new diversified ensemble learning scheme
J Bi, C Zhang - Knowledge-Based Systems, 2018 - Elsevier
Class-imbalance learning is one of the most challenging problems in machine learning. As a
new and important direction in this field, multi-class imbalanced data classification has …
new and important direction in this field, multi-class imbalanced data classification has …
Progress of artificial neural networks applications in hydrogen production
The demand for green energy is expanding, and it seems that hydrogen is the best option
that can be produced and stored in large quantities. Hydrogen is a promising energy carrier …
that can be produced and stored in large quantities. Hydrogen is a promising energy carrier …
Mining product innovation ideas from online reviews
The importance of online customer reviews to product innovation has been well-recognized
in prior literature. Mining online reviews has received extensive attention and efforts. Most …
in prior literature. Mining online reviews has received extensive attention and efforts. Most …
The machine learning-based dropout early warning system for improving the performance of dropout prediction
A dropout early warning system enables schools to preemptively identify students who are at
risk of dropping out of school, to promptly react to them, and eventually to help potential …
risk of dropping out of school, to promptly react to them, and eventually to help potential …