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Improving the Analysis of MINI-LINK Test Data Using Unsupervised Machine Learning
Nerella, Dinesh Kumar
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
2023 (English)
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
Student thesis
Place, publisher, year, edition, pages
2023. , p. 54
Keywords [en]
Unsupervised machine learning, Clustering
National Category
Computer Sciences
Identifiers
URN:
urn:nbn:se:bth-24952
OAI: oai:DiVA.org:bth-24952
DiVA, id:
diva2:1773927
External cooperation
Ericsson, Borås
Subject / course
DV2572 Master´s Thesis in Computer Science
Educational program
DVADA Master Qualification Plan in Computer Science
Supervisors
Josyula, Sai Prashanth
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
Examiners
Mendes, Emilia
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
Available from:
2023-06-27
Created:
2023-06-24
Last updated:
2023-06-27
Bibliographically approved
Open Access in DiVA
Improving the Analysis of MINI-LINK Test Data Using Unsupervised Machine Learning
(1395 kB)
132 downloads
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FULLTEXT02.pdf
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f26e45bf7f449ef7fc9223acc8b47c374a2b7d8a80c7e422a82ac919f1f1c4141b3c966d2070032d42b3e855d75a54e99c91dabb9679eda820f885b553cb6540
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Computer Sciences
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Total: 132 downloads
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ieee
modern-language-association-8th-edition
vancouver
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modern-language-association-8th-edition
vancouver
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