Sobol Sensitivity: A Strategy for Feature Selection

DOI10.1007/978-3-319-46310-0_4zbMath1367.68221OpenAlexW2581151838MaRDI QIDQ5268903

No author found.

Publication date: 21 June 2017

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-46310-0_4

zbMATH Keywords

sensitivity analysismachine learningfeature selectionSobol index

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

FORECASTING STOCK MARKET CRASHES VIA REAL-TIME RECESSION PROBABILITIES: A QUANTUM COMPUTING APPROACH

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• The Adaptive Lasso and Its Oracle Properties
• Feature extraction. Foundations and applications. Papers from NIPS 2003 workshop on feature extraction, Whistler, BC, Canada, December 11--13, 2003. With CD-ROM.
• Principles and theory for data mining and machine learning
• The jackknife estimate of variance
• Multivariate adaptive regression splines
• Estimating the dimension of a model
• Least angle regression. (With discussion)
• Variable importance in binary regression trees and forests
• Better Subset Regression Using the Nonnegative Garrote
• Maximum likelihood identification of Gaussian autoregressive moving average models
• 10.1162/153244303322753616
• Regularization and Variable Selection Via the Elastic Net
• On the representation of continuous functions of several variables by superpositions of continuous functions of a smaller number of variables
• On the Non-Negative Garrotte Estimator
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Variable Selection in Data Mining
• Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates
• Random forests
• A new look at the statistical model identification

This page was built for publication: Sobol Sensitivity: A Strategy for Feature Selection