Results 21 to 30 of about 796,511 (318)
Structure Preserving Non-negative Feature Self-Representation for Unsupervised Feature Selection
IEEE Access, 2017 Inspired by the importance of self-representation and structure-preserving ability of features, in this paper, we propose a novel unsupervised feature selection algorithm named structure-preserving non-negative feature self-representation (SPNFSR).
Wei Zhou +3 more
doaj +1 more source
New Feature Selection Algorithm Based on Feature Stability and Correlation
IEEE Access, 2022 The analysis of a large amount of data with high dimensionality of rows and columns increases the load of machine learning algorithms. Such data are likely to have noise and consequently, obstruct the performance of machine learning algorithms.
Luai Al-Shalabi
doaj +1 more source
A lexicographic multi-objective genetic algorithm for multi-label correlation-based feature selection [PDF]
, 2015 This paper proposes a new Lexicographic multi-objective Genetic Algorithm for Multi-Label Correlation-based Feature Selection (LexGA-ML-CFS), which is an extension of the previous single-objective Genetic Algorithm for Multi-label Correlation-based ...
Suwimol Jungjit +3 more
core +1 more source
Feature extraction for epileptic seizure detection using machine learning
Current Medicine Research and Practice, 2020 Background: Epilepsy is a common neurological disorder and affects approximately 70 million people worldwide. The traditional approach used by neurologists for the detection of seizure is time consuming.
Renuka Mohan Khati, Rajesh Ingle
doaj +1 more source
Quadratic Mutual Information Feature Selection
Entropy, 2017 We propose a novel feature selection method based on quadratic mutual information which has its roots in Cauchy–Schwarz divergence and Renyi entropy. The method uses the direct estimation of quadratic mutual information from data samples using Gaussian ...
Davor Sluga, Uroš Lotrič
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Metalearning for Feature Selection
CoRR, 2017 A general formulation of optimization problems in which various candidate solutions may use different feature-sets is presented, encompassing supervised classification, automated program learning and other cases. A novel characterization of the concept of a "good quality feature" for such an optimization problem is provided; and a proposal regarding ...
Ben Goertzel +2 more
openaire +2 more sources
Feature Selection in Automatic Music Genre Classification [PDF]
, 2008 This paper presents the results of the application of a feature selection procedure to an automatic music genre classification system. The classification system is based on the use of multiple feature vectors and an ensemble approach, according to time ...
Celso A. A. Kaestner +5 more
core +1 more source
Semi-supervised Partial Multi-label Feature Selection [PDF]
Jisuanji kexueMulti-label feature selection is a technique for reducing feature dimensionality by filtering out a subset of features with distinguishing power from the original feature space.However,the traditional method faces the problem of labeling accuracy ...
WU You, WANG Jing, LI Peipei, HU Xuegang
doaj +1 more source
CBFS: high performance feature selection algorithm based on feature clearness. [PDF]
PLoS ONE, 2012 BACKGROUND: The goal of feature selection is to select useful features and simultaneously exclude garbage features from a given dataset for classification purposes.
Minseok Seo, Sejong Oh
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torkar/feature-selection-RBS: Zenodo release
, 2021 Replication pkg for manuscript on feature selection in requirements ...
Richard Torkar
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