bfunc

Compute upper bound of second derivative of loss.

internal

Functional gradient descent algorithm for a variety of convex and non-convex loss functions, for both classical and robust regression and classification problems. See Wang (2011) <doi:10.2202/1557-4679.1304>, Wang (2012) <doi:10.3414/ME11-02-0020>, Wang (2018) <doi:10.1080/10618600.2018.1424635>, Wang (2018) <doi:10.1214/18-EJS1404>.

Zhu Wang

Gradient Boosting

Torsten Hothorn

bfunc function

<dl> <dt>family</dt>
<dd>a family from "closs", "gloss", "qloss" for classification and "clossR" for robust regression.</dd> <dt>s</dt>
<dd>a parameter related to robustness.</dd></dl>

Arguments

Author

Compute upper bound of second derivative of loss — bfunc

<dl>

 <dt>family</dt>
<dd>a family from "closs", "gloss", "qloss" for classification and "clossR" for robust regression.</dd>

 <dt>s</dt>
<dd>a parameter related to robustness.</dd>

</dl>

bfunc: Compute upper bound of second derivative of loss

Description

Usage

Value

Arguments

Author

Details