A comprehensive survey for intelligent spam email detection
The tremendously growing problem of phishing e-mail, also known as spam including spear
phishing or spam borne malware, has demanded a need for reliable intelligent anti-spam e …
phishing or spam borne malware, has demanded a need for reliable intelligent anti-spam e …
A review on ensembles for the class imbalance problem: bagging-, boosting-, and hybrid-based approaches
Classifier learning with data-sets that suffer from imbalanced class distributions is a
challenging problem in data mining community. This issue occurs when the number of …
challenging problem in data mining community. This issue occurs when the number of …
Features dimensionality reduction approaches for machine learning based network intrusion detection
The security of networked systems has become a critical universal issue that influences
individuals, enterprises and governments. The rate of attacks against networked systems …
individuals, enterprises and governments. The rate of attacks against networked systems …
Credit card fraud detection under extreme imbalanced data: a comparative study of data-level algorithms
Credit card fraud is one of the biggest cybercrimes faced by users. Intelligent machine
learning based fraudulent transaction detection systems are very effective in real-world …
learning based fraudulent transaction detection systems are very effective in real-world …
Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics
Class imbalance is among the most persistent complications which may confront the
traditional supervised learning task in real-world applications. The problem occurs, in the …
traditional supervised learning task in real-world applications. The problem occurs, in the …
Classification of imbalanced ECG beats using re-sampling techniques and AdaBoost ensemble classifier
Computer-aided heartbeat classification has a significant role in the diagnosis of cardiac
dysfunction. Electrocardiogram (ECG) provides vital information about the heartbeats. In this …
dysfunction. Electrocardiogram (ECG) provides vital information about the heartbeats. In this …
An empirical evaluation of sampling methods for the classification of imbalanced data
M Kim, KB Hwang - PLoS One, 2022 - journals.plos.org
In numerous classification problems, class distribution is not balanced. For example, positive
examples are rare in the fields of disease diagnosis and credit card fraud detection. General …
examples are rare in the fields of disease diagnosis and credit card fraud detection. General …
Discrimination of COPD and lung cancer from controls through breath analysis using a self-developed e-nose
VA Binson, M Subramoniam… - Journal of Breath …, 2021 - iopscience.iop.org
This work details the application of a metal oxide semiconductor (MOS) sensor based
electronic nose (e-nose) system in the discrimination of lung cancer and chronic obstructive …
electronic nose (e-nose) system in the discrimination of lung cancer and chronic obstructive …
Detecting financial misstatements with fraud intention using multi-class cost-sensitive learning
YJ Kim, B Baik, S Cho - Expert systems with applications, 2016 - Elsevier
We develop multi-class financial misstatement detection models to detect misstatements
with fraud intention. Hennes, Leone and Miller (2008) conducted a post-event analysis of …
with fraud intention. Hennes, Leone and Miller (2008) conducted a post-event analysis of …
[HTML][HTML] Explaining customer churn prediction in telecom industry using tabular machine learning models
The study addresses customer churn, a major issue in service-oriented sectors like
telecommunications, where it refers to the discontinuation of subscriptions. The research …
telecommunications, where it refers to the discontinuation of subscriptions. The research …