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Advancing financial analytics: Integrating XGBoost, LSTM, and Random Forest Algorithms for precision forecasting of corporate financial distress
Research article (Journal of Infrastructure Policy and Development, 2024) · cited 13× · AI/ML
Advancing financial analytics: Integrating XGBoost, LSTM, and Random Forest Algorithms for precision forecasting of corporate financial distress
Summary
Advancing financial analytics: Integrating XGBoost, LSTM, and Random Forest Algorithms for precision forecasting of corporate financial distress is a scholarly article[1].
Key Facts
Advancing financial analytics: Integrating XGBoost, LSTM, and Random Forest Algorithms for precision forecasting of corporate financial distress's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Advancing financial analytics: Integrating XGBoost, LSTM, and Random Forest Algorithms for precision forecasting of corporate financial distress. Retrieved May 24, 2026, from https://4ort.xyz/entity/advancing-financial-analytics-integrating-xgboost-lstm-and-random-forest-algorithms-for-precision-forecasting-of-corpora
MLA“Advancing financial analytics: Integrating XGBoost, LSTM, and Random Forest Algorithms for precision forecasting of corporate financial distress.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/advancing-financial-analytics-integrating-xgboost-lstm-and-random-forest-algorithms-for-precision-forecasting-of-corpora.
BibTeX@misc{4ortxyz_advancing-financial-analytics-integrating-xgboost-lstm-and-random-forest-algorithms-for-precision-forecasting-of-corpora_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Advancing financial analytics: Integrating XGBoost, LSTM, and Random Forest Algorithms for precision forecasting of corporate financial distress}}, year = {2026}, url = {https://4ort.xyz/entity/advancing-financial-analytics-integrating-xgboost-lstm-and-random-forest-algorithms-for-precision-forecasting-of-corpora}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Advancing financial analytics: Integrating XGBoost, LSTM, and Random Forest Algorithms for precision forecasting of corporate financial distress — https://4ort.xyz/entity/advancing-financial-analytics-integrating-xgboost-lstm-and-random-forest-algorithms-for-precision-forecasting-of-corpora (retrieved 2026-05-24)
