Naive Bayes: applications, variations and vulnerabilities: a review of literature with code snippets for implementation
I Wickramasinghe, H Kalutarage - Soft Computing, 2021 - Springer
Naïve Bayes (NB) is a well-known probabilistic classification algorithm. It is a simple but
efficient algorithm with a wide variety of real-world applications, ranging from product …
efficient algorithm with a wide variety of real-world applications, ranging from product …
Some bibliometric procedures for analyzing and evaluating research fields
Nowadays, measuring the quality and quantity of the scientific production is an important
necessity since almost every research assessment decision depends, to a great extent …
necessity since almost every research assessment decision depends, to a great extent …
A review on method entities in the academic literature: Extraction, evaluation, and application
In scientific research, the method is an indispensable means to solve scientific problems and
a critical research object. With the advancement of sciences, many scientific methods are …
a critical research object. With the advancement of sciences, many scientific methods are …
A feature dependent Naive Bayes approach and its application to the software defect prediction problem
Naive Bayes is one of the most widely used algorithms in classification problems because of
its simplicity, effectiveness, and robustness. It is suitable for many learning scenarios, such …
its simplicity, effectiveness, and robustness. It is suitable for many learning scenarios, such …
Solving multi-criteria group decision making problems under environments with a high number of alternatives using fuzzy ontologies and multi-granular linguistic …
JA Morente-Molinera, G Kou… - Knowledge-Based …, 2017 - Elsevier
Classic multi-criteria group decision making models that have a high amount of alternatives
are unmanageable for the experts. This is because they have to provide one value per each …
are unmanageable for the experts. This is because they have to provide one value per each …
A survey on dynamic mobile malware detection
P Yan, Z Yan - Software Quality Journal, 2018 - Springer
The outstanding advances of mobile devices stimulate their wide usage. Since mobile
devices are coupled with third-party applications, lots of security and privacy problems are …
devices are coupled with third-party applications, lots of security and privacy problems are …
An enhanced ensemble learning-based fault detection and diagnosis for grid-connected PV systems
The main objective of this article is to develop an enhanced ensemble learning (EL) based
intelligent fault detection and diagnosis (FDD) paradigms that aim to ensure the high …
intelligent fault detection and diagnosis (FDD) paradigms that aim to ensure the high …
TSK fuzzy system fusion at sensitivity-ensemble-level for imbalanced data classification
Previous studies have shown that the performance of a classifier on imbalanced data
heavily relies on informative objects lying in borderline or overlapping areas. In this study …
heavily relies on informative objects lying in borderline or overlapping areas. In this study …
Investigation of the performance of machine learning classifiers for pneumonia detection in chest X-ray images
Pneumonia is one of the serious and life-threatening diseases that is caused by a bacterial
or viral infection of the lungs and have the potential to result in severe consequences within …
or viral infection of the lungs and have the potential to result in severe consequences within …
A deep-ensemble-level-based interpretable Takagi–Sugeno–Kang fuzzy classifier for imbalanced data
Existing research reveals that the misclassification rate for imbalanced data depends heavily
on the problematic areas due to the existence of small disjoints, class overlap, borderline …
on the problematic areas due to the existence of small disjoints, class overlap, borderline …