A survey on evolutionary multiobjective feature selection in classification: approaches, applications, and challenges
Maximizing the classification accuracy and minimizing the number of selected features are
two primary objectives in feature selection, which is inherently a multiobjective task …
two primary objectives in feature selection, which is inherently a multiobjective task …
Towards the design of vision-based intelligent vehicle system: methodologies and challenges
Rapid growth in technology has changed the way humans live. Ongoing development in the
automobile industry is creating intelligent vehicles and this mode of transportation will assist …
automobile industry is creating intelligent vehicles and this mode of transportation will assist …
QQLMPA: A quasi-opposition learning and Q-learning based marine predators algorithm
Many engineering and scientific problems in the real-world boil down to optimization
problems, which are difficult to solve by using traditional methods. Meta-heuristics are …
problems, which are difficult to solve by using traditional methods. Meta-heuristics are …
A survey on human activity recognition using deep learning techniques and wearable sensor data
HAR has attained major attention because of its significant use in real-life scenarios like
activity and fitness monitoring, rehabilitation, gaming, prosthetic limbs, healthcare, smart …
activity and fitness monitoring, rehabilitation, gaming, prosthetic limbs, healthcare, smart …
Population characteristic exploitation-based multi-orientation multi-objective gene selection for microarray data classification
M Li, R Cao, Y Zhao, Y Li, S Deng - Computers in Biology and Medicine, 2024 - Elsevier
Gene selection is a process of selecting discriminative genes from microarray data that
helps to diagnose and classify cancer samples effectively. Swarm intelligence evolution …
helps to diagnose and classify cancer samples effectively. Swarm intelligence evolution …
A recursive framework for improving the performance of multi-objective differential evolution algorithms for gene selection
M Li, Y Zhao, R Cao, J Wang, D Wu - Swarm and Evolutionary …, 2024 - Elsevier
Gene selection is a pivotal process in machine-learning-driven medical diagnostics, where
the goal is to identify a subset of genes from microarray expression profiles that can …
the goal is to identify a subset of genes from microarray expression profiles that can …
A graph based preordonnances theoretic supervised feature selection in high dimensional data
Generally, for high-dimensional datasets, only some features are relevant, while others are
irrelevant or redundant. In the machine learning field, the use of a strategy for eliminating …
irrelevant or redundant. In the machine learning field, the use of a strategy for eliminating …
Maximal cliques-based hybrid high-dimensional feature selection with interaction screening for regression
H Chamlal, A Benzmane, T Ouaderhman - Neurocomputing, 2024 - Elsevier
Studies on feature selection have been extensively conducted in the literature, as it plays a
significant role in both supervised and unsupervised machine learning tasks. Since the bulk …
significant role in both supervised and unsupervised machine learning tasks. Since the bulk …
Multi-strategy improved sand cat optimization algorithm-based workflow scheduling mechanism for heterogeneous edge computing environment
Edge computing is one of the predominant technologies which facilitates the option of
bringing out the computing resources closer to the location of the end users when they are …
bringing out the computing resources closer to the location of the end users when they are …
A multiform optimization framework for multi-objective feature selection in classification
Feature selection in machine learning as a key data processing technique has two
conflicting goals: minimizing the classification error rate and minimizing the number of …
conflicting goals: minimizing the classification error rate and minimizing the number of …