@inproceedings{c2a0694e95304a58aa519e01f379d53b,
title = "Sparse Group Lasso for regression on land climate variables",
abstract = "The large amount of reliable climate data available today has promoted the development of statistical predictive models for climate variables. In this paper we have applied Sparse Group Lasso to build a predictive model for land climate variables using ocean climate variables as covariates.We demonstrate that the sparse model provides better predictive performance than the state-of-the-art, is climatologically interpretable and robust in variable selection.",
keywords = "Climate prediction, Sparse Group Lasso, Sparse regression",
author = "Soumyadeep Chatterjee and Arindam Banerjee and Chatterjee, {Singdhansu B} and Ganguly, {Auroop R.}",
year = "2011",
doi = "10.1109/ICDMW.2011.155",
language = "English (US)",
isbn = "9780769544090",
series = "Proceedings - IEEE International Conference on Data Mining, ICDM",
pages = "1--8",
booktitle = "Proceedings - 11th IEEE International Conference on Data Mining Workshops, ICDMW 2011",
note = "11th IEEE International Conference on Data Mining Workshops, ICDMW 2011 ; Conference date: 11-12-2011 Through 11-12-2011",
}