A new framework of multi-objective evolutionary algorithms for feature selection and multi-label classification of video data
There are few studies in the literature to address the multi-objective multi-label feature
selection for the classification of video data using evolutionary algorithms. Selecting the …
selection for the classification of video data using evolutionary algorithms. Selecting the …
Feature selection using multi-objective CHC genetic algorithm
S Rathee, S Ratnoo - Procedia Computer Science, 2020 - Elsevier
Most of the datasets contain redundancies and inconsistencies in terms of features or
instances or both. Therefore, datasets always need pre-processing before applying data …
instances or both. Therefore, datasets always need pre-processing before applying data …
Population-Based Meta-heuristics for Feature Selection: A Multi-objective Perspective
J Ahuja, S Ratnoo - Proceedings of International Conference on Data …, 2023 - Springer
There exists an ample number of meta-heuristics for feature subset selection in data mining
literature. Most of these algorithms have been restructured to employ multi-objective …
literature. Most of these algorithms have been restructured to employ multi-objective …
Detection of glaucoma in retinal images based on multiobjective approach
Glaucoma is one of the major causes of blindness. Glaucoma is a condition due to
increased pressure within the eyeball, causing progressive, irreversible and gradual loss of …
increased pressure within the eyeball, causing progressive, irreversible and gradual loss of …
Genetic algorithm with different feature selection method for intrusion detection
N Cleetus, KA Dhanya - 2014 First International Conference on …, 2014 - ieeexplore.ieee.org
Intrusion detection is used to protect the system from inside and outside attacks.
Evolutionary algorithm has an important role in intrusion detection. Evolutionary algorithms …
Evolutionary algorithm has an important role in intrusion detection. Evolutionary algorithms …
Feature selection via pareto multi-objective genetic algorithms
Feature selection, an important combinatorial optimization problem in data mining, aims to
find a reduced subset of features of high quality in a dataset. Different categories of …
find a reduced subset of features of high quality in a dataset. Different categories of …
[HTML][HTML] 基于自适应遗传算法的入侵检测特征选择方法
李安, 江加和 - 2016 - html.rhhz.net
针对网络入侵检测所处理数据特征维数高, 入侵检测系统负荷大, 检测速度慢等问题,
提出了一种将自适应遗传算法与信息增益相结合的特征选择方法, 并采用基于支持向量机的分类 …
提出了一种将自适应遗传算法与信息增益相结合的特征选择方法, 并采用基于支持向量机的分类 …
Exploration of two-objective scenarios on supervised evolutionary feature selection: A survey and a case study (application to music categorisation)
I Vatolkin - … Optimization: 8th International Conference, EMO 2015 …, 2015 - Springer
Almost all studies which apply feature selection for supervised classification are limited to
single-objective optimisation, validating feature sets with only one criterion like accuracy …
single-objective optimisation, validating feature sets with only one criterion like accuracy …
FFS: A F-Dbscan clustering-based feature selection for classification Data
N Eshaghi, A Aghagolzadeh - Journal of Advances in Computer …, 2017 - jacr.sari.iau.ir
Feature selection is an important step in most classification problems to select an optimal
subset of features to increase the learning accuracy and reduce the computational time. In …
subset of features to increase the learning accuracy and reduce the computational time. In …
Dual data selection using multi-objective Micro-CHC
S Rathee, S Ratnoo - Recent Advances in Computer Science …, 2021 - ingentaconnect.com
Objective: Redundant and superfluous features or instances reduce the efficiency and
efficacy of data mining algorithms. Hence, selecting relevant and significant features and …
efficacy of data mining algorithms. Hence, selecting relevant and significant features and …