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Machine Learning and Synthetic Minority Oversampling Techniques for Imbalanced Data: Improving Machine Failure Prediction

Yap Bee Wah, Azlan Ismail, Nur Niswah Naslina Azid, Jafreezal Jaafar, Izzatdin Abdul Aziz, Mohd Hilmi Hasan, Jasni Mohamad Zain

2023Computers, materials & continua/Computers, materials & continua (Print)13 citationsDOIOpen Access PDF

Abstract

Prediction of machine failure is challenging as the dataset is often imbalanced with a low failure rate. The common approach to handle classification involving imbalanced data is to balance the data using a sampling approach ... | Find, read and cite all the research you need on Tech Science Press

Topics & Concepts

OversamplingSupport vector machineUndersamplingNaive Bayes classifierArtificial intelligenceMachine learningComputer scienceRandom forestSensitivity (control systems)Test dataPattern recognition (psychology)Data miningEngineeringBandwidth (computing)Programming languageElectronic engineeringComputer networkImbalanced Data Classification TechniquesElectricity Theft Detection TechniquesFinancial Distress and Bankruptcy Prediction
Machine Learning and Synthetic Minority Oversampling Techniques for Imbalanced Data: Improving Machine Failure Prediction | Litcius