print.cv.npcs

We connect the multi-class Neyman-Pearson classification (NP) problem to the cost-sensitive learning (CS) problem, and propose two algorithms (NPMC-CX and NPMC-ER) to solve the multi-class NP problem through cost-sensitive learning tools. Under certain conditions, the two algorithms are shown to satisfy multi-class NP properties. More details are available in the paper "Neyman-Pearson Multi-class Classification via Cost-sensitive Learning" (Ye Tian and Yang Feng, 2021).

Ching-Tsung Tsai

npcs

Neyman-Pearson Classification via Cost-Sensitive Learning

Ye Tian

Yang Feng

print.cv.npcs function

<dl><dt>x</dt>
<dd>fitted cv.npcs object using <code>cv.npcs</code>.</dd>
<dt>...</dt>
<dd>additional arguments.</dd></dl>

Arguments

Print the cv.npcs object. — print.cv.npcs

<dl>

<dt>x</dt>
<dd>fitted cv.npcs object using <code>cv.npcs</code>.</dd>


<dt>...</dt>
<dd>additional arguments.</dd>

</dl>

print.cv.npcs: Print the cv.npcs object.

Description

Usage

Arguments