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  • Search: subject:"ensemble learning methods"
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Year of publication
Subject
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Ensemble learning methods 2 AUC 1 Artificial intelligence 1 Benchmark dataset analysis 1 Benchmarking 1 Classification 1 Classification accuracy improvement 1 Confident learning 1 Credit risk 1 Data quality 1 Data quality enhancement 1 Datenqualität 1 Evaluation parameters 1 Followers 1 Forecasting model 1 Klassifikation 1 Kreditrisiko 1 Künstliche Intelligenz 1 Label noise detection 1 Link prediction 1 Product labelling 1 Prognoseverfahren 1 Quality management 1 Qualitätsmanagement 1 Social network 1 Theorie 1 Theory 1 Warenkennzeichnung 1 discriminatory power 1 ensemble learning methods 1 loss given default 1 partial least squares algorithm 1 random forest 1 stochastic gradient boosting 1
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Online availability
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Undetermined 2 CC license 1 Free 1
Type of publication
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Article 3
Type of publication (narrower categories)
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Article in journal 2 Aufsatz in Zeitschrift 2 research-article 1
Language
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English 3
Author
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Bhattacharya, Riju 1 Jin, Zi 1 Nagwani, Naresh Kumar 1 Sun, Han Sheng 1 Tripathi, Sarsij 1 Zheng, Wanwan 1
Published in...
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Data Technologies and Applications 1 The journal of credit risk : published quarterly by Incisive Media 1
Source
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ECONIS (ZBW) 2 Other ZBW resources 1
Showing 1 - 3 of 3
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A shadow-based framework for label noise detection and data quality enhancement
Zheng, Wanwan - 2025
Machine learning algorithms are typically evaluated using benchmark datasets under the assumption that these datasets are clean. However, recent studies have revealed the presence of label noise in many benchmark datasets, indicating a biased evaluation to date. Confident learning (CL), an...
Persistent link: https://www.econbiz.de/10015420492
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A hybrid approach for predicting missing follower–followee links in social networks using topological features with ensemble learning
Bhattacharya, Riju; Nagwani, Naresh Kumar; Tripathi, Sarsij - In: Data Technologies and Applications 57 (2023) 1, pp. 131-153
hybrid features on data sets. This was followed by using benchmark classifiers and ensemble learning methods. The experiments …
Persistent link: https://www.econbiz.de/10014712628
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Estimating credit risk parameters using ensemble learning methods : an empirical study on loss given default
Sun, Han Sheng; Jin, Zi - In: The journal of credit risk : published quarterly by … 12 (2016) 3, pp. 43-69
Persistent link: https://www.econbiz.de/10011643773
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