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Found 3 papers, 1 papers with code
Survival regression with accelerated failure time model in XGBoost
In this work, we implement loss functions for learning accelerated failure time (AFT) models in XGBoost, to increase the support for survival modeling for different kinds of label censoring.
Network Elastic Net for Identifying Smoking specific gene expression for lung cancer
Our aim is to identify smoking specific gene expression biomarkers in the prognosis of lung cancer patients.
Stacking with Neural network for Cryptocurrency investment
Features used are technical indicators used are not limited to trend, momentum, volume, volatility indicators, and sentiment analysis has also been used to gain useful insight combined with the above features.
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