Calibrated Boosting-Forest

Summary

Calibrated Boosting-Forest offers a benchmark demonstration that in the field of ligand-based virtual screening, deep learning is not the universally dominant machine learning model and good calibrated probabilities can better facilitate virtual screening process.

Keywords

Gradient boosting, Boosting (machine learning), Machine learning, Artificial intelligence, Computer science

References

Stacked generalizationDavid H. Wolpert — 1992
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiersBianca Zadrozny, Charles Elkan — 2001
The Comparison and Evaluation of Forecasters.Morris H. DeGroot, Stephen E. Fienberg — 1983
Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likelihood MethodsJohn Platt — 1999
Greedy function approximation: A gradient boosting machine.Jerome H. Friedman — 2001
Extended-Connectivity FingerprintsDavid Rogers, Mathew Hahn — 2010
Current Trends in Ligand-Based Virtual Screening: Molecular Representations, Data Mining Methods, New Application Areas, and Performance EvaluationHanna Geppert, Martin Vogt, Jürgen Bajorath — 2010
A CROC stronger than ROC: measuring, visualizing and optimizing early retrievalS. Joshua Swamidass, Chloé‐Agathe Azencott, Kenny Daily — 2010
XGBoost: A Scalable Tree Boosting SystemTianqi Chen, Carlos Guestrin — 2016
MoleculeNet: a benchmark for molecular machine learningZhenqin Wu, Bharath Ramsundar, Evan N. Feinberg — 2017
Random ForestsLeo Breiman — 2001
Stacked regressionsLeo Breiman — 2004
Journal of Chemical Information and ModelingWilliam L. Jorgensen — 2005
Obtaining Calibrated Probabilities from BoostingAlexandru Niculescu-Mizil, Rich Caruana — 2005
Regularization and Variable Selection Via the Elastic NetHui Zou, Trevor Hastie — 2005
Variable SelectionBastian Goldluecke, Variational Method, Velvety Reﬂectance — 2019

Cited by

No citing papers recorded for this paper.

Related papers

Gradient Boosting Machine: A SurveyZhiyuan He, Danchen Lin, Thomas Lau — 2019
Sales Prediction of Big Mart based on Linear Regression, Random Forest, and Gradient BoostingRuiyun Kang — 2023
Accelerated proximal boostingErwan Fouillen, Claire Boyer, Maxime Sangnier — 2018
Gradient and Newton Boosting for Classification and RegressionFabio Sigrist — 2018
A Survey of Ensemble Learning: Concepts, Algorithms, Applications, and ProspectsIbomoiye Domor Mienye, Yanxia Sun — 2022
An Ensemble of Random Forest Gradient Boosting Machine and Deep Learning Methods for Stock Price PredictionLokesh Kumar Shrivastav, Ravinder Kumar — 2022