A hybrid feature selection method to improve performance of a group of classification algorithms
M Naseriparsa, AM Bidgoli, T Varaee - arXiv preprint arXiv:1403.2372, 2014 - arxiv.org
In this paper a hybrid feature selection method is proposed which takes advantages of
wrapper subset evaluation with a lower cost and improves the performance of a group of …
wrapper subset evaluation with a lower cost and improves the performance of a group of …
[PDF][PDF] Feature selection methods: Case of filter and wrapper approaches for maximising classification accuracy.
Feature selection has been widely applied in many areas such as classification of spam
emails, cancer cells, fraudulent claims, credit risk, text categorisation and DNA microarray …
emails, cancer cells, fraudulent claims, credit risk, text categorisation and DNA microarray …
[PDF][PDF] A Hybrid filter-wrapper approach for FeatureSelection
S NAQVI - 2011 - diva-portal.org
Feature selection is the task of selecting a small subset from original features that can
achieve maximum classification accuracy. This subset of features has some very important …
achieve maximum classification accuracy. This subset of features has some very important …
A methodology for improving the performance of non-ranker feature selection filters
Feature selection is the process of identifying relevant features in the dataset and discarding
everything else as irrelevant and redundant. Since feature selection reduces the …
everything else as irrelevant and redundant. Since feature selection reduces the …
Hybrid filter-wrapper feature selection using whale optimization algorithm: A multi-objective approach
Feature selection aims at finding the minimum number of features that result in high
classification accuracy. Accordingly, the feature selection is considered as a multi-objective …
classification accuracy. Accordingly, the feature selection is considered as a multi-objective …
[图书][B] Feature selection by combining multiple methods
Feature selection is the process of identifying relevant features in the dataset and discarding
everything else as irrelevant and redundant. Since feature selection reduces the …
everything else as irrelevant and redundant. Since feature selection reduces the …
[HTML][HTML] A new feature selection method based on a validity index of feature subset
C Liu, W Wang, Q Zhao, X Shen, M Konan - Pattern Recognition Letters, 2017 - Elsevier
The wrapper feature selection method can achieve high classification accuracy. However,
the cross-validation scheme of the wrapper method in evaluation phase is very expensive …
the cross-validation scheme of the wrapper method in evaluation phase is very expensive …
[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 …
Feature selection using hierarchical feature clustering
One of the challenges in data mining is the dimensionality of data, which is often very high
and prevalent in many domains, such as text categorization and bio-informatics. The high …
and prevalent in many domains, such as text categorization and bio-informatics. The high …
A comprehensive comparison on evolutionary feature selection approaches to classification
Feature selection is an important data preprocessing step in machine learning and data
mining, such as classification tasks. Research on feature selection has been extensively …
mining, such as classification tasks. Research on feature selection has been extensively …