Zobrazeno 1 - 10
of 112
pro vyhledávání: '"Supervised data"'
Autor:
Shakir Fattah Kak
Publikováno v:
Eurasian Journal of Science and Engineering, Vol 9, Iss 3, Pp 209-219 (2023)
In accordance with the proverb "a picture is worth a thousand words," facial expressions have the ability to convey a wide range of emotions depending on the circumstances. Observing facial expressions during face-to-face interactions allows us to in
Externí odkaz:
https://doaj.org/article/b7f373f4d05d4067bccaecfc91ce8158
Akademický článek
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Autor:
Abhishek Subramanian, Pooya Zakeri, Mira Mousa, Halima Alnaqbi, Fatima Yousif Alshamsi, Leo Bettoni, Ernesto Damiani, Habiba Alsafar, Yvan Saeys, Peter Carmeliet
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 20, Iss , Pp 5235-5255 (2022)
Multi-omics technologies are being increasingly utilized in angiogenesis research. Yet, computational methods have not been widely used for angiogenic target discovery and prioritization in this field, partly because (wet-lab) vascular biologists are
Externí odkaz:
https://doaj.org/article/a93dd39e2a824c218011b6f107cb27fe
Publikováno v:
Energy and Built Environment, Vol 1, Iss 2, Pp 149-164 (2020)
With the advent of the era of big data, buildings have become not only energy-intensive but also data-intensive. Data mining technologies have been widely utilized to release the values of massive amounts of building operation data with an aim of imp
Externí odkaz:
https://doaj.org/article/6db5c81a73de4e4090d512cd8382c563
Publikováno v:
Sensors, Vol 23, Iss 3, p 1520 (2023)
In the era of big data, industrial process data are often generated rapidly in the form of streams. Thus, how to process such sequential and high-speed stream data in real time and provide critical quality variable predictions has become a critical i
Externí odkaz:
https://doaj.org/article/7a3c6c061db44e8cb850c5e42d67454e
Akademický článek
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Publikováno v:
Mathematics, Vol 10, Iss 20, p 3734 (2022)
In this paper, we study the regularized Huber regression algorithm in a reproducing kernel Hilbert space (RKHS), which is applicable to both fully supervised and semi-supervised learning schemes. Our focus in the work is two-fold: first, we provide t
Externí odkaz:
https://doaj.org/article/94271598eeeb446e849d03f828d71643
Autor:
Nur Uylaş Satı
Publikováno v:
Pamukkale University Journal of Engineering Sciences, Vol 24, Iss 5, Pp 864-869 (2018)
Semi-supervised data classification is one of significant field of study in machine learning and data mining since it deals with datasets which consists both a few labeled and many unlabeled data. The researchers have interest in this field because i
Externí odkaz:
https://doaj.org/article/021c86c2f5874c3584c7c7f43120c243
Autor:
Nur Uylaş Satı
Publikováno v:
Pamukkale University Journal of Engineering Sciences, Vol 24, Iss 5, Pp 864-869 (2018)
Yarı-gözetimli veri sınıflandırma, makine öğrenme ve veri madenciliğinde önemli bir çalışma alanıdır çünkü az sayıda etiketli ve çok sayıda etiketsiz veri içeren veri kümeleri ile ilgilenmektedir. Gerçek hayat veri kümelerinin
Externí odkaz:
https://doaj.org/article/3f1e8d5c98c34c3ebc6db049a26f086a
Publikováno v:
IEEE Access, Vol 5, Pp 6600-6607 (2017)
This paper presents a supervised data imputation based on the class-dependent matrix factors, which are generated during matrix factorization. The proposed ridge alternating least squares imputation uses class information to create substituted values
Externí odkaz:
https://doaj.org/article/387d2bb30e4a4aa5af2fa2f70017cf51