arXiv:2404.02184
공식 코드 · Papers with Code
What is to be gained by ensemble models in analysis of spectroscopic data?
원문 초록
An empirical study was carried out to compare different implementations of ensemble models aimed at improving prediction in spectroscopic data. A wide range of candidate models were fitted to benchmark datasets from regression and classification settings. A statistical analysis using linear mixed model was carried out on prediction performance criteria resulting from model fits over random splits of the data. The results showed that the ensemble classifiers were able to consistently outperform candidate models in our application
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Why Regression? Binary Encoding Classification Brings Confidence to Stock Market Index Price Prediction
Gaussian Process Regression With Interpretable Sample-Wise Feature Weights
Prediction of Chronic Kidney Disease - A Machine Learning Perspective
Efficient energy consumption prediction model for a data analytic-enabled industry building in a smart city
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