Comparison of tuned ensemble using SA and GA with untuned ensemble and AutoML.

<p>Comparison of tuned ensemble using SA and GA with untuned ensemble and AutoML.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Ali Bahrami (20700339) (author)
مؤلفون آخرون:	Morteza Rakhshaninejad (20700342) (author), Rouzbeh Ghousi (9389125) (author), Alireza Atashi (5053763) (author)
منشور في:	2025
الموضوعات:	Biotechnology Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified xgboost &# 8212 utilized simulated annealing models &# 8212 intensive care unit artificial neural networks model performance underscores require ventilators immediately ml models constructing fundamental need within cardiac surgery icu tuned ensemble model ensemble model xlink "> vital topic supported breathing study examines significant improvement rich source potential goldmine massive volume machine learning limited availability informative analyses hyperparameter optimization hybrid approach healthcare professionals healthcare industry genetic algorithm deep learning crucial consideration approach enhanced ann ), 84 %,
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