grid.gen

grid.gen: generate grid for cross-validation function. For internal package use only.

Implements L0-constrained Multi-Task Learning and domain generalization algorithms. The algorithms are coded in Julia allowing for fast implementations of the coordinate descent and local combinatorial search algorithms. For more details, see a preprint of the paper: Loewinger et al., (2022) <arXiv:2212.08697>.

Gabriel Loewinger

sMTL

Sparse Multi-Task Learning

Kayhan Behdin

Giovanni Parmigiani

Rahul Mazumder

National Science Foundation Grant DMS1810829

National Science Foundation Grant DMS2113707

National Science Foundation Grant NSF-IIS1718258,

Office of Naval Research Grant ONR N000142112841

National Institute on Drug Abuse (NIH) Grant F31DA052153

grid.gen function

<dl><dt>y</dt>
<dd>A numeric vector or matrix of outcomes</dd>
<dt>p</dt>
<dd>An integer of covariate dimension</dd>
<dt>study</dt>
<dd>An integer vector of task IDs</dd>
<dt>lambda_1</dt>
<dd>A boolean</dd>
<dt>lambda_2</dt>
<dd>A boolean</dd>
<dt>lambda_z</dt>
<dd>A boolean</dd>
<dt>commonSupp</dt>
<dd>A boolean</dd>
<dt>multiTask</dt>
<dd>A boolean</dd></dl>

Arguments

grid.gen: generate grid for cross-validation function. For internal package use only. — grid.gen

<dl>

<dt>y</dt>
<dd>A numeric vector or matrix of outcomes</dd>


<dt>p</dt>
<dd>An integer of covariate dimension</dd>


<dt>study</dt>
<dd>An integer vector of task IDs</dd>


<dt>lambda_1</dt>
<dd>A boolean</dd>


<dt>lambda_2</dt>
<dd>A boolean</dd>


<dt>lambda_z</dt>
<dd>A boolean</dd>


<dt>commonSupp</dt>
<dd>A boolean</dd>


<dt>multiTask</dt>
<dd>A boolean</dd>

</dl>

grid.gen: generate grid for cross-validation function. For internal package use only.

grid.gen: grid.gen: generate grid for cross-validation function. For internal package use only.

Description

Usage

Value

Arguments