Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Benjamin Denham"'
Publikováno v:
Proceedings of the VLDB Endowment. 15:2334-2347
Effective supervised training of modern machine learning models often requires large labelled training datasets, which could be prohibitively costly to acquire for many practical applications. Research addressing this problem has sought ways to lever
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4468b8de96dcde04575d05ec6f252200
https://doi.org/10.14778/3551793.3551797
https://doi.org/10.14778/3551793.3551797
Publikováno v:
2021 IEEE International Conference on Data Mining (ICDM).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bc45fa9075ca4edb007aa85b8761f254
https://doi.org/10.1109/icdm51629.2021.00121
https://doi.org/10.1109/icdm51629.2021.00121
Publikováno v:
ICDM
Datasets containing class noise present significant challenges to accurate classification, thus requiring classifiers that can refuse to classify noisy instances. We demonstrate the inability of the popular confidence-thresholding rejection method to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bbfc92728d0634ef80d7d94340168452
https://doi.org/10.1109/icdm50108.2020.00114
https://doi.org/10.1109/icdm50108.2020.00114
Publikováno v:
International Journal of Software Engineering and Knowledge Engineering. 28:663-700
Evaluating software modules for inclusion in a Drupal website is a crucial and complex task that currently requires manual assessment of a number of module facets. This study applied data-mining techniques to identify quality-related metrics associat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d25fc109b506a2d42c19b9c69d53173
https://doi.org/10.1142/s0218194018500195
https://doi.org/10.1142/s0218194018500195
Publikováno v:
Expert Systems with Applications. 152:113380
The sensitive nature of many data streams necessitates data mining techniques that are privacy-preserving. This paper proposes two data perturbation methods for privacy-preserving stream mining based on a combination of random projection, random tran
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::66e8ce7b8afccdc5120b26c259bdfb06
https://doi.org/10.1016/j.eswa.2020.113380
https://doi.org/10.1016/j.eswa.2020.113380
Publikováno v:
Knowledge-Based Systems. 189:105114
The rise in the Internet of Things (IoT) and other sensor networks has created many vertically-distributed and high-velocity data streams that require specialized algorithms for true distributed data mining. This paper proposes a novel Hierarchical D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d584928895d3c919a49659f51004e67f
https://doi.org/10.1016/j.knosys.2019.105114
https://doi.org/10.1016/j.knosys.2019.105114
