ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
ABSTRACT: The integration of artificial intelligence into the development and production of mechatronic products offers a substantial opportunity to enhance efficiency, adaptability, and system ...
Abstract: Hyperparameter recommendation via meta-learning has shown great promise in various studies. The main challenge for meta-learning is how to develop an effective meta-learner (learning ...
Abstract: In recent years, battery degradation has become a critical concern in various industries, including electric vehicles, renewable energy systems, and portable electronics. To address this ...
We publish the best academic work (that's too often lost to peer reviews & the TA's desk) to the global tech community byEScholar: Electronic Academic Papers for Scholars@escholar byEScholar: ...
In machine learning, algorithms harness the power to unearth hidden insights and predictions from within data. Central to the effectiveness of these algorithms are hyperparameters, which can be ...
Hi, so this isn't as much of a bug as a question I have about LGBM. I am tuning hyperparameters with 3-fold cross validation for an LGBM classifier on a dataset that has about 2 million samples with ...
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