createWeightBasedSearchControl

<code>createWeightBasedSearchControl</code> creates a Cyclops control object for use with <code>fitCyclopsModel</code>
that supports hyperparameter optimization through an auto-search where weight = 1 identifies in-sample observations
and weight = 0 identifies out-of-sample observations.

This model fitting tool incorporates cyclic coordinate descent and
majorization-minimization approaches to fit a variety of regression models
found in large-scale observational healthcare data. Implementations focus
on computational optimization and fine-scale parallelization to yield
efficient inference in massive datasets. Please see:
Suchard, Simpson, Zorych, Ryan and Madigan (2013) <doi:10.1145/2414416.2414791>.

Marc A Suchard

Cyclops

Cyclic Coordinate Descent for Logistic, Poisson and Survival
Analysis

Marc A. Suchard

Martijn J. Schuemie

Trevor R. Shaddox

Yuxi Tian

Jianxiao Yang

Eric Kawaguchi

Sushil Mittal

Observational Health Data Sciences and Informatics 

Marcus Geelnard

Rutgers University 

R Development Core Team 

createWeightBasedSearchControl function

<dl><dt>cvType</dt>
<dd>Must equal "auto"</dd>
<dt>initialValue</dt>
<dd>Initial value for auto-search parameter</dd>
<dt>...</dt>
<dd>Additional parameters passed through to <code>createControl</code></dd></dl>

Arguments

Create a Cyclops control object that supports in- / out-of-sample hyperparameter search using weights — createWeightBasedSearchControl

<dl>

<dt>cvType</dt>
<dd>Must equal "auto"</dd>


<dt>initialValue</dt>
<dd>Initial value for auto-search parameter</dd>


<dt>...</dt>
<dd>Additional parameters passed through to <code>createControl</code></dd>

</dl>

Create a Cyclops control object that supports in- / out-of-sample hyperparameter search using weights

createWeightBasedSearchControl: Create a Cyclops control object that supports in- / out-of-sample hyperparameter search using weights

Description

Usage

Value

Arguments