Results 1 to 10 of about 28,744 (310)

Elastic Net Regularization Paths for All Generalized Linear Models [PDF]

Journal of Statistical Software, 2023
The lasso and elastic net are popular regularized regression models for supervised learning. Friedman, Hastie, and Tibshirani (2010) introduced a computationally efficient algorithm for computing the elastic net regularization path for ordinary least ...
J. Kenneth Tay, Balasubramanian Narasimhan, Trevor Hastie   +2 more
doaj   +8 more sources

Efficient Elastic Net Regularization for Sparse Linear Models [PDF]

, 2015
This paper presents an algorithm for efficient training of sparse linear models with elastic net regularization. Extending previous work on delayed updates, the new algorithm applies stochastic gradient updates to non-zero features only, bringing weights
Elkan, Charles, Lipton, Zachary C.
core   +4 more sources

Pyglmnet : Python implementation of elastic-net regularized generalized linear models [PDF]

Journal of Open Source Software, 2020
Graceful handling of small Hessian term in coordinate descent solver that led to exploding update term Ensure full compatibility of GLM class with scikit ...
Achakulvisut, Titipat, Acuna, Daniel, Agrawal, Mayank, Antalek, Matthew, De Toni, Giovanni, Dyer, Eva, Fernandes, Hugo, Foley, Peter, Garg, Ravi Prakash, Hamalainen, Matti, Harris, Drew, Idrizović, Aid, Jas, Mainak, Kording, Konrad, Li, Beibin, Marques, Vinicius, Odland, Tommy, Otterson, Scott, Pieters, Olivier, Ramkumar, Pavan, Rodgers, Chris, Umegaki, Yu   +21 more
core   +6 more sources

Elastic-Net Regularization: Error estimates and Active Set Methods [PDF]

Inverse Problems, 2009
This paper investigates theoretical properties and efficient numerical algorithms for the so-called elastic-net regularization originating from statistics, which enforces simultaneously l^1 and l^2 regularization.
Attouch H, Bangti Jin, Bonesky T, Burger M, Dirk A Lorenz, Engl H W, Grasmair M, Griesse R, Jin B Zou J, Lee H, Loris I, Rockafellar R T, Stefan Schiffler, Tibshirani R   +13 more
core   +5 more sources

An Application of Elastic-Net Regularized Linear Inverse Problem in Seismic Data Inversion [PDF]

Applied Sciences, 2023
In exploration geophysics, seismic impedance is a physical characteristic parameter of underground formations. It can mark rock characteristics and help stratigraphic analysis.
Ronghuo Dai, Cheng Yin, Da Peng
doaj   +2 more sources

kppmenet: combining the kppm and elastic net regularization for inhomogeneous Cox point process with correlated covariates. [PDF]

J Appl Stat, 2023
Choiruddin A, Yuni Susanto T, Husain A, Mega Kartikasari Y.   +3 more
europepmc   +3 more sources

Development and validation of hybrid machine learning approach for predicting survival in patients with cervical cancer: a SEER-based population study [PDF]

Frontiers in Oncology
BackgroundAccurate survival prediction in cervical cancer is crucial for personalized therapy, particularly in high-risk groups where early intervention might enhance results.
Anjana Eledath Kolasseri, Venkataramana B.   +1 more
doaj   +2 more sources

Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent [PDF]

Journal of Statistical Software, 2011
We introduce a pathwise algorithm for the Cox proportional hazards model, regularized by convex combinations of l1 and l2 penalties (elastic net). Our algorithm fits via cyclical coordinate descent, and employs warm starts to find a solution along a ...
Noah Simon, Jerome Friedman, Trevor Hastie, Rob Tibshirani   +3 more
doaj   +1 more source

Regularization Paths for Generalized Linear Models via Coordinate Descent [PDF]

Journal of Statistical Software, 2010
We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multi- nomial regression problems while the penalties include ℓ1 (the lasso), ℓ2 (ridge
Jerome Friedman, Trevor Hastie, Rob Tibshirani   +2 more
doaj   +1 more source

Evaluating key predictors of breast cancer through survival: a comparison of AFT frailty models with LASSO, ridge, and elastic net regularization. [PDF]

BMC Cancer
Bosson-Amedenu S, Ayitey E, Ayiah-Mensah F, Asare L.   +3 more
europepmc   +3 more sources