Results 11 to 20 of about 2,965,444 (278)
Weighted Pseudo Labeled Data and Mutual Learning for Semi-Supervised Classification
IEEE Access, 2021 In this article, a semi-supervised classification algorithm that is based on weighted pseudo labeled data and mutual learning is proposed. The purpose of our method is to improve the classification performance of semi-supervised learning models and ...
Jianwen Mo, Yuwan Gan, Hua Yuan
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A residential labeled dataset for smart meter data analytics
Scientific Data, 2022 Measurement(s) Electricity Consumption Technology Type(s) Transformer Device Sample Characteristic - Location ...
Lucas Pereira +2 more
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Improved Machine Reading Comprehension Using Data Validation for Weakly Labeled Data
IEEE Access, 2020 Machine reading comprehension (MRC) is a natural language processing task wherein a given question is answered according to a holistic understanding of a given context.
Yunyeong Yang, Sangwoo Kang, Jungyun Seo
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Issues in Data Labelling [PDF]
, 2010 Labelling emotion databases is not a purely technical matter. It is bound up with theoretical issues. Different issues affect labelling of emotional content, labelling of the signs that convey emotion, and labelling of the relevant context. Linked to these are representational issues, involving time course, consensus and divergence, and connections ...
Cowie, Roddy +5 more
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GAN-BElectra: Enhanced Multi-class Sentiment Analysis with Limited Labeled Data
Applied Artificial Intelligence, 2022 Performing sentiment analysis with high accuracy using machine-learning techniques requires a large quantity of training data. However, getting access to such a large quantity of labeled data for specific domains can be expensive and time-consuming ...
Md. Riyadh, M. Omair Shafiq
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Excentric Labeling: Dynamic Neighborhood Labeling for Data Visualization [PDF]
Proceedings of the SIGCHI conference on Human factors in computing systems the CHI is the limit - CHI '99, 1999 The widespread use of information visualization is hampered by the lack of effective labeling techniques. An informal taxonomy of labeling methods is proposed. We then describe “excentric labeling”, a new dynamic technique to label a neighborhood of objects located around the cursor.
Jean-Daniel Fekete, Catherine Plaisant
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Application of biclustering algorithm to extract rules from labeled data [PDF]
International Journal of Crowd Science, 2018 Purpose - For many pattern recognition problems, the relation between the sample vectors and the class labels are known during the data acquisition procedure.
Zhang Yanjie, Sun Hongbo
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A multi-label classification method for disposing incomplete labeled data and label relevance
Dianxin kexue, 2016 Multi-label classification methods have been applied in many real-world fields，in which the labels may have strong relevance and some of them even are incomplete or missing.However，existing multi-label classification algorithms are unable to handle both ...
Lina ZHANG, Lingpeng DAI, Tai KUANG
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Beyond Hard Labels: Investigating data label distributions
, 2022 High-quality data is a key aspect of modern machine learning. However, labels generated by humans suffer from issues like label noise and class ambiguities. We raise the question of whether hard labels are sufficient to represent the underlying ground truth distribution in the presence of these inherent imprecision.
Grossmann, Vasco +2 more
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Labeled entities from social media data related to avian influenza disease
Data in Brief, 2022 This dataset is composed by spatial (e.g. location) and thematic (e.g. diseases, symptoms, virus) entities concerning avian influenza in social media (textual) data in English.
Camille Schaeffer +4 more
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