Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Fares Grina"'
Publikováno v:
International Journal of Approximate Reasoning. 156:1-15
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::39b92d2a46736260459a9241455a7f4b
https://doi.org/10.1016/j.ijar.2023.02.006
https://doi.org/10.1016/j.ijar.2023.02.006
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031188428
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a55826163b159268181c549a7387b958
https://doi.org/10.1007/978-3-031-18843-5_16
https://doi.org/10.1007/978-3-031-18843-5_16
Publikováno v:
Information Processing and Management of Uncertainty in Knowledge-Based Systems ISBN: 9783031089732
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb59e99e47c50f972a8b8ba62f415651
https://doi.org/10.1007/978-3-031-08974-9_49
https://doi.org/10.1007/978-3-031-08974-9_49
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030867713
ECSQARU
ECSQARU
Class imbalance is a common issue in many real world classification problems. It refers to situations where the number of observations in the training dataset significantly differs for each class. Ignoring this issue will make it more challenging for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2b792084b71f52e949f0baf54859f094
https://doi.org/10.1007/978-3-030-86772-0_25
https://doi.org/10.1007/978-3-030-86772-0_25
Publikováno v:
Modeling Decisions for Artificial Intelligence ISBN: 9783030855284
MDAI
MDAI
The class imbalance issue involves many real-world domains such as fraud detection, medical diagnosis, intrusion detection, etc. Most classification algorithms tend to perform poorly when the training dataset is class-imbalanced. This problem gets mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5a764e0303ca348adbad2ec221182e8
https://doi.org/10.1007/978-3-030-85529-1_15
https://doi.org/10.1007/978-3-030-85529-1_15
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030623647
IDEAL (2)
IDEAL (2)
Dealing with imbalanced datasets at the preprocessing level is an efficient strategy used by many methods to re-balance the data and improve classification performance. Specifically, SMOTE is a popular oversampling technique which modifies the traini
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6d1f6bb17f6ed6f06b53707355891d64
https://doi.org/10.1007/978-3-030-62365-4_1
https://doi.org/10.1007/978-3-030-62365-4_1