A DBN-based resampling SVM ensemble learning paradigm for credit classification with imbalanced data
Summary
A DBN-based resampling SVM ensemble learning paradigm for credit classification with imbalanced data is a scholarly article[1].
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A DBN-based resampling SVM ensemble learning paradigm for credit classification with imbalanced data's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). A DBN-based resampling SVM ensemble learning paradigm for credit classification with imbalanced data. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-dbn-based-resampling-svm-ensemble-learning-paradigm-for-credit-classification-with-imbalanced-data
BibTeX@misc{4ortxyz_a-dbn-based-resampling-svm-ensemble-learning-paradigm-for-credit-classification-with-imbalanced-data_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A DBN-based resampling SVM ensemble learning paradigm for credit classification with imbalanced data}}, year = {2026}, url = {https://4ort.xyz/entity/a-dbn-based-resampling-svm-ensemble-learning-paradigm-for-credit-classification-with-imbalanced-data}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A DBN-based resampling SVM ensemble learning paradigm for credit classification with imbalanced data — https://4ort.xyz/entity/a-dbn-based-resampling-svm-ensemble-learning-paradigm-for-credit-classification-with-imbalanced-data (retrieved 2026-05-24)
