enpls.mae

An algorithmic framework for measuring feature importance,
outlier detection, model applicability domain evaluation,
and ensemble predictive modeling with (sparse)
partial least squares regressions.

Nan Xiao

enpls

Ensemble Partial Least Squares Regression

Dong-Sheng Cao

Miao-Zhu Li

Qing-Song Xu

enpls.mae function

<dl><dt>yreal</dt>
<dd>true response vector</dd>
<dt>ypred</dt>
<dd>predicted response vector</dd></dl>

Arguments

Nan Xiao &lt;<a href="https://nanx.me">https://nanx.me</a>&gt;

Author

Mean Absolute Error (MAE) — enpls.mae

<dl>

<dt>yreal</dt>
<dd>true response vector</dd>


<dt>ypred</dt>
<dd>predicted response vector</dd>

</dl>

Nan Xiao &lt;<a href='https://nanx.me'>https://nanx.me</a>&gt;

enpls.mae: Mean Absolute Error (MAE)

Description

Usage

Value

Arguments

Author