kneedle

An internal function utilized by VSOLassoBag.

A wrapped LASSO approach by integrating an ensemble learning strategy to help select efficient, stable, and high confidential variables from omics-based data. Using a bagging strategy in combination of a parametric method or inflection point search method for cut-off threshold determination. This package can integrate and vote variables generated from multiple LASSO models to determine the optimal candidates. Luo H, Zhao Q, et al (2020) <doi:10.1126/scitranslmed.aax7533> for more details.

Chaoye Wang

VSOLassoBag

Variable Selection Oriented LASSO Bagging Algorithm

Jiaqi Liang

kneedle function

<dl><dt>res</dt>
<dd>a dataframe with variables and observed frequency</dd>
<dt>S</dt>
<dd>numeric, determines how aggressive the elbow points on the curve to be called, smaller means more aggressive and larger means more conservative</dd>
<dt>auto.loose</dt>
<dd>if TRUE, will reduce `kneedle.S` in case no elbow point is found with the set `kneedle.S`</dd>
<dt>min.S</dt>
<dd>a numeric value determines the minimal value that `kneedle.S` will be loosed to.</dd>
<dt>loosing.factor</dt>
<dd>a numeric value range in (0,1), which `kneedle.S` is multiplied by to reduce itself.</dd></dl>

Arguments

Kneedle Algorithm: to detect elbow point(s) on the curve — kneedle

<dl>

<dt>res</dt>
<dd>a dataframe with variables and observed frequency</dd>


<dt>S</dt>
<dd>numeric, determines how aggressive the elbow points on the curve to be called, smaller means more aggressive and larger means more conservative</dd>


<dt>auto.loose</dt>
<dd>if TRUE, will reduce `kneedle.S` in case no elbow point is found with the set `kneedle.S`</dd>


<dt>min.S</dt>
<dd>a numeric value determines the minimal value that `kneedle.S` will be loosed to.</dd>


<dt>loosing.factor</dt>
<dd>a numeric value range in (0,1), which `kneedle.S` is multiplied by to reduce itself.</dd>

</dl>

kneedle: Kneedle Algorithm: to detect elbow point(s) on the curve

Description

Usage

Value

Arguments

References

Examples