[HTML][HTML] A new univariate feature selection algorithm based on the best–worst multi-attribute decision-making method
DPM Abellana, DM Lao - Decision Analytics Journal, 2023 - Elsevier
With the extensive applicability of machine learning classification algorithms to a wide
spectrum of domains, feature selection (FS) becomes a relevant data preprocessing …
spectrum of domains, feature selection (FS) becomes a relevant data preprocessing …
A feature selection method based on ranked vector scores of features for classification
F Kamalov, F Thabtah - Annals of Data Science, 2017 - Springer
One of the major aspects of any classification process is selecting the relevant set of features
to be used in a classification algorithm. This initial step in data analysis is called the feature …
to be used in a classification algorithm. This initial step in data analysis is called the feature …
A multi-objective optimization algorithm for feature selection problems
B Abdollahzadeh, FS Gharehchopogh - Engineering with Computers, 2022 - Springer
Feature selection (FS) is a critical step in data mining, and machine learning algorithms play
a crucial role in algorithms performance. It reduces the processing time and accuracy of the …
a crucial role in algorithms performance. It reduces the processing time and accuracy of the …
[PDF][PDF] Single feature ranking and binary particle swarm optimisation based feature subset ranking for feature selection
This paper proposes two wrapper based feature selection approaches, which are single
feature ranking and binary particle swarm optimisation (BPSO) based feature subset …
feature ranking and binary particle swarm optimisation (BPSO) based feature subset …
Ensemble of feature selection algorithms: a multi-criteria decision-making approach
A Hashemi, MB Dowlatshahi… - International Journal of …, 2022 - Springer
For the first time, the ensemble feature selection is modeled as a Multi-Criteria Decision-
Making (MCDM) process in this paper. For this purpose, we used the VIKOR method as a …
Making (MCDM) process in this paper. For this purpose, we used the VIKOR method as a …
A new hybrid feature selection based on multi-filter weights and multi-feature weights
Y Wang, L Feng - Applied Intelligence, 2019 - Springer
A traditional feature selection of filters evaluates the importance of a feature by using a
particular metric, deducing unstable performances when the dataset changes. In this paper …
particular metric, deducing unstable performances when the dataset changes. In this paper …
Feature selection algorithm using relative odds for data mining classification
DD Atsa'am - Big data analytics for sustainable computing, 2020 - igi-global.com
A filter feature selection algorithm is developed and its performance tested. In the initial step,
the algorithm dichotomizes the dataset then separately computes the association between …
the algorithm dichotomizes the dataset then separately computes the association between …
Tri-staged feature selection in multi-class heterogeneous datasets using memetic algorithm and cuckoo search optimization
Classification algorithms and their preprocessing operations usually performs on feature
selection on homogeneous or heterogeneous attributes, binary or multi-class labels …
selection on homogeneous or heterogeneous attributes, binary or multi-class labels …
[PDF][PDF] Toward optimal feature selection using ranking methods and classification algorithms
J Novaković - Yugoslav Journal of operations research, 2016 - yujor.fon.bg.ac.rs
We presented a comparison between several feature ranking methods used on two real
datasets. We considered six ranking methods that can be divided into two broad categories …
datasets. We considered six ranking methods that can be divided into two broad categories …
All-relevant feature selection using multidimensional filters with exhaustive search
K Mnich, WR Rudnicki - Information Sciences, 2020 - Elsevier
This paper describes a method for the identification of informative variables in an information
system with discrete decision variables. It is targeted specifically towards the discovery of …
system with discrete decision variables. It is targeted specifically towards the discovery of …