Articles with "multiclass classification" as a keyword



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Multiclass Classification Based on Multi-criteria Decision-making

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Published in 2019 at "Journal of Classification"

DOI: 10.1007/s00357-018-9286-6

Abstract: Lots of real-world problems require multiclass classification. Since most general classification methods are originally introduced for binary problems (including two classes), they should be extended to multiclass problems. A solution proposed for multiclass problems is… read more here.

Keywords: criteria decision; classification; decision making; multiclass ... See more keywords
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Risk upper bounds for general ensemble methods with an application to multiclass classification

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Published in 2017 at "Neurocomputing"

DOI: 10.1016/j.neucom.2016.09.016

Abstract: This paper generalizes a pivotal result from the PAC-Bayesian literature -the C - bound - primarily designed for binary classification to the general case of ensemble methods of voters with arbitrary outputs. We provide a… read more here.

Keywords: risk; classification; multiclass classification; bound ... See more keywords
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Multiclass classification of dephasing channels

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Published in 2021 at "Physical Review A"

DOI: 10.1103/physreva.104.052412

Abstract: Adriano M. Palmieri, ∗ Federico Bianchi, † Matteo G. A. Paris, 4, ‡ and Claudia Benedetti § Skolkovo Institute of Science and Technology, 121205 Moscow, Russia Bocconi University, I-20136 Milan, Italy. Quantum Technology Lab, Dipartimento… read more here.

Keywords: milano; classification dephasing; multiclass classification; dephasing channels ... See more keywords
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An Evolutionary Multitasking Method for Multiclass Classification

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Published in 2022 at "IEEE Computational Intelligence Magazine"

DOI: 10.1109/mci.2022.3199625

Abstract: As an important research topic of machine learning, multiclass classification has wide applications ranging from computer vision to bioinformatics. A variety of multiclass classification algorithms with promising performance have been proposed. Among them, the decomposition-based… read more here.

Keywords: classification; evolutionary multitasking; multiclass; method ... See more keywords
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Multiclass Classification of Cardiac Arrhythmia Using Improved Feature Selection and SVM Invariants

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Published in 2018 at "Computational and Mathematical Methods in Medicine"

DOI: 10.1155/2018/7310496

Abstract: Arrhythmia is considered a life-threatening disease causing serious health issues in patients, when left untreated. An early diagnosis of arrhythmias would be helpful in saving lives. This study is conducted to classify patients into one… read more here.

Keywords: arrhythmia; multiclass classification; svm; feature selection ... See more keywords
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3D convolutional neural networks-based multiclass classification of Alzheimer’s and Parkinson’s diseases using PET and SPECT neuroimaging modalities

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Published in 2021 at "Brain Informatics"

DOI: 10.1186/s40708-021-00144-2

Abstract: Background Alzheimer’s disease (AD) is a neurodegenerative brain pathology formed due to piling up of amyloid proteins, development of plaques and disappearance of neurons. Another common subtype of dementia like AD, Parkinson’s disease (PD) is… read more here.

Keywords: classification; multiclass classification; convolutional neural; using pet ... See more keywords
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Natural Language Processing Approaches for Automated Multilevel and Multiclass Classification of Breast Lesions on Free-Text Cytopathology Reports.

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Published in 2022 at "JCO clinical cancer informatics"

DOI: 10.1200/cci.22.00036

Abstract: PURPOSE The extensive growth and use of electronic health records (EHRs) and extending medical literature have led to huge opportunities to automate the extraction of relevant clinical information that helps in concise and effective clinical… read more here.

Keywords: multilevel multiclass; classification; breast lesions; multiclass classification ... See more keywords
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A Tensorized Multitask Deep Learning Network for Progression Prediction of Alzheimer’s Disease

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Published in 2022 at "Frontiers in Aging Neuroscience"

DOI: 10.3389/fnagi.2022.810873

Abstract: With the advances in machine learning for the diagnosis of Alzheimer’s disease (AD), most studies have focused on either identifying the subject’s status through classification algorithms or on predicting their cognitive scores through regression methods,… read more here.

Keywords: classification; alzheimer disease; multiclass classification; prediction ... See more keywords