Results 261 to 270 of about 4,317,504 (301)

Multi-Label Classification for Past Events

2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI), 2018
Study and analysis of past events can provide numerous benefits. While event categorization has been previously studied, it was usually assigned only one event category to an event. In this work we focus on multi-label classification for past events that is a more general and challenging problem than the previous studies.
Yasunobu Sumikawa, Ryohei Ikejiri
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Multi-label classification for Oil Authentication

2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, 2012
Oil Authentication influences the life of the human being substantially. In tradition, NIR (near infrared ray) is followed by the single-label learning or the feature transformation to distinguish the pure oil and the mixed oil. In our work, we adopt the multi-label AdaBoost.RMH algorithm to proceed the chromatographic images of edible oil from high ...
Quan-gong Huo, Xiao-Bo Jin, Hong-mei Zhang   +2 more
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Empirical Studies on Multi-label Classification

2006 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'06), 2006
In classic pattern recognition problems, classes are mutually exclusive by definition. However, in many applications, it is quite natural that some instances belong to multiple classes at the same time. In other words, these applications are multi-labeled, classes are overlapped by definition and each instance may be associated to multiple classes.
Tao Li 0001, Chengliang Zhang, Shenghuo Zhu   +2 more
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Discriminative Methods for Multi-labeled Classification

2004
In this paper we present methods of enhancing existing discriminative classifiers for multi-labeled predictions. Discriminative methods like support vector machines perform very well for uni-labeled text classification tasks. Multi-labeled classification is a harder task subject to relatively less attention.
GODBOLE, S, SARAWAGI, S
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Multi-label Classification of Anemia Patients

2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA), 2015
This work examines the application of machine learning to an important area of medicine which aims to diagnose paediatric patients with s -- thalassemia minor, iron deficiency anemia or the co-occurrence of these ailments. Iron deficiency anemia is a major cause of microcytic anemia and is considered an important task in global health.
Colin Bellinger, Ali Amid, Nathalie Japkowicz, Herna L. Viktor   +3 more
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Reduced-rank multi-label classification

Statistics and Computing, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ting Yuan, Junhui Wang
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Metric Learning for Multi-label Classification

2021
This paper proposes an approach for multi-label classification based on metric learning. The approach has been designed to deal with general classification problems, without any assumption on the specific kind of data used (images, text, etc.) or semantic meaning assigned to labels (tags, categories, etc.). It is based on clustering and metric learning
Marco Brighi, Annalisa Franco, Dario Maio   +2 more
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Multi-label Document Classification in Czech

2013
This paper deals with multi-label automatic document classification in the context of a real application for the Czech news agency. The main goal of this work is to compare and evaluate three most promising multi-label document classification approaches on a Czech language. We show that the simple method based on a meta-classifier proposes by Zhu at al.
Michal Hrala, Pavel Král
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Multi-label classification with Bayes' theorem

2011 4th International Conference on Biomedical Engineering and Informatics (BMEI), 2011
Compared with single-label classification, multi-label classification is more general in practice, since it allows one instance to have more than one label simultaneously. Bayes' Theorem has been successfully applied to deal with single-label classification. In this paper, we proposed to tackle multi-label classification using Bayes' Theorem.
Guangzhi Qu, Hui Zhang, Craig T. Hartrick   +2 more
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Label Expansion for Multi-label Classification

2018 7th Brazilian Conference on Intelligent Systems (BRACIS), 2018
In multi-label classification tasks, instances are simultaneously associated with multiple labels, representing different and, possibly, related concepts from a domain. One characteristic of these tasks is a high class-label imbalance. In order to obtain improved predictive models, several algorithms either have explored the label dependencies or have ...
Adriano Rivolli, Carlos Soares, André C. P. L. F. de Carvalho   +2 more
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