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trainClassifier_KNN_A.m (5.75 kB)

trainClassifier_KNN_A.m

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Version 4 2022-10-26, 16:58
Version 3 2022-10-22, 10:54
Version 2 2022-09-17, 15:40
Version 1 2022-09-17, 12:52
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posted on 2022-10-26, 16:58 authored by DAVID CASCALES FULGENCIODAVID CASCALES FULGENCIO

k-Nearest Neighbours model trained with frequency- and time-domain features extracted from the Case Western Reserve University (CWRU) signals database.

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    Keywords

    Rolling Element Bearing Fault Diagnosis ApproachMachine Learningk-Nearest Neighbours (KNN)Mechanical Engineering

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    CC BY 4.0

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