predict.npcs

Predict new labels from new data based on the fitted NPMC classifier, which belongs to S3 class "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

predict.npcs function

<dl><dt>object</dt>
<dd>the model object for prediction</dd>
<dt>newx</dt>
<dd>input feature data</dd>
<dt>...</dt>
<dd>arguments to pass down</dd></dl>

Arguments

Predict new labels from new data based on the fitted NPMC classifier. — predict.npcs

<dl>

<dt>object</dt>
<dd>the model object for prediction</dd>


<dt>newx</dt>
<dd>input feature data</dd>


<dt>...</dt>
<dd>arguments to pass down</dd>

</dl>

predict.npcs: Predict new labels from new data based on the fitted NPMC classifier.

Description

Usage

Arguments