solid-package: A Divide-and-Conquer Method for Sparse Risk Prediction and...
In ChuanHong/solid-copy: A Divide-and-Conquer Method for Sparse Risk Prediction and Evaluation
Description
The package solid consists 1) a screening and one-step linearization infused DAC (SOLID) algorithm to fit sparse logistic regression to massive datasets, and 2) a modified cross-validation (MCV) that utilizes the side products of the SOLID hence substantially reduce the computational burden.
Details
Package: solid
Type: Package
Version: 1.1
Date: 2019-11-06
License: GPL>=2
Author(s)
Chuan Hong
Yan Wang
Tianxi Cai
Maintainer: Chuan Hong <chuan_hong@hms.harvard.edu>
ChuanHong/solid-copy documentation built on Dec. 17, 2021, 2:05 p.m.
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Description
The package solid consists 1) a screening and one-step linearization infused DAC (SOLID) algorithm to fit sparse logistic regression to massive datasets, and 2) a modified cross-validation (MCV) that utilizes the side products of the SOLID hence substantially reduce the computational burden.
Details
| Package: | solid |
| Type: | Package |
| Version: | 1.1 |
| Date: | 2019-11-06 |
| License: GPL>=2 | |
Author(s)
Chuan Hong
Yan Wang
Tianxi Cai
Maintainer: Chuan Hong <chuan_hong@hms.harvard.edu>
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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