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Erschienen in:
Deep Learning Short-Time Interval Passenger Flow Prediction Based on Isomap Algorithm Kapitel lesen Erstes Kapitel lesen

2022 | OriginalPaper | Buchkapitel

14. QUasi-Affine TRansformation Evolutionary Algorithm for Feature Selection

verfasst von : Zhi-Gang Du, Tien-Szu Pan, Jeng-Shyang Pan, Shu-Chuan Chu

Erschienen in: Advances in Smart Vehicular Technology, Transportation, Communication and Applications

Verlag: Springer Singapore

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Abstract

QUasi-Affine TRansformation Evolutionary Algorithm (QUATRE) is a currently emerging meta-heuristic evolutionary algorithm. QUATRE has the ability to balance exploitation and exploration in the optimization process, and the algorithm optimization uses matrix operations to greatly reduce the time complexity for solving the same problem. This series of advantages makes this algorithm adopted by a large number of researchers. In this paper, QUATRE is used to optimize the Feature Selection (FS) of the wrapper method. K-Fold Cross-Validation (KFCV) method is also used to divide the test set and training set of the sample, and then use the K Nearest Neighbor (KNN) algorithm for feature classification. In the optimization process, we use a threshold (choice) for feature identification to select useful features. Finally, the 9 standard test data sets in UCI are used to verify the effectiveness of the QUATRE algorithm.

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Vorheriges Kapitel Event Sequence T-Way Test Strategy for Events Driven System
Nächstes Kapitel Advanced QUasi-Affine TRansformation Evolutionary (QUATRE) Algorithm and Its Application for Neural Network
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Metadaten
Titel
QUasi-Affine TRansformation Evolutionary Algorithm for Feature Selection
verfasst von
Zhi-Gang Du
Tien-Szu Pan
Jeng-Shyang Pan
Shu-Chuan Chu
Copyright-Jahr
2022
Verlag
Springer Singapore
Buch
Advances in Smart Vehicular Technology, Transportation, Communication and Applications

Print ISBN: 978-981-16-4038-4

Electronic ISBN: 978-981-16-4039-1

Copyright-Jahr: 2022

DOI
https://doi.org/10.1007/978-981-16-4039-1_14

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