Neighborhood rough set reduction with fish swarm algorithm
Sign Up to like & getrecommendations! Published in 2017 at "Soft Computing"
DOI: 10.1007/s00500-016-2393-6
Abstract: Feature reduction refers to the problem of deleting those input features that are less predictive of a given outcome; a problem encountered in many areas such as pattern recognition, machine learning and data mining. In… read more here.
Keywords: reduction; feature reduction; rough set; neighborhood rough ... See more keywords
Graph classification based on graph set reconstruction and graph kernel feature reduction
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DOI: 10.1016/j.neucom.2018.03.029
Abstract: Abstract Graph, a kind of structured data, is widely used to model complex relationships among objects, and has been used in various of scientific and engineering fields, such as bioinformatics, network intrusion detection, social network,… read more here.
Keywords: classification; graph set; graph classification; graph kernel ... See more keywords
Feature reduction based on semantic similarity for graph classification
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DOI: 10.1016/j.neucom.2020.02.047
Abstract: Abstract Classification and recognition of graph data are crucial problems in many fields, such as bioinformatics, chemoinformatics and data mining. In graph kernel-based classification methods, the similarity among substructures is not fully considered; in addition,… read more here.
Keywords: graph classification; feature reduction; classification; similarity ... See more keywords
Empirical Analysis of Feature Reduction in Deep Learning and Conventional Methods for Foot Image Classification
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DOI: 10.1109/access.2021.3069625
Abstract: Deep learning algorithms are employed in many applications, especially in medical fields such as gait analysis and human pose detection for rehabilitation. However, creating the desired model with deep learning algorithms requires high memory and… read more here.
Keywords: feature reduction; conventional methods; deep learning; empirical analysis ... See more keywords
UC-Merced Image Classification with CNN Feature Reduction Using Wavelet Entropy Optimized with Genetic Algorithm
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DOI: 10.18280/ts.370301
Abstract: Received: 2 February 2020 Accepted: 26 April 2020 The classification of high-resolution and remote sensed terrain images with high accuracy is one of the greatest challenges in machine learning. In the present study, a novel… read more here.
Keywords: classification; entropy; cnn feature; reduction using ... See more keywords