ppCoderN

Please see <a href="https://win-vector.com/2017/09/25/custom-level-coding-in-vtreat/">https://win-vector.com/2017/09/25/custom-level-coding-in-vtreat/</a> and
<a href="https://win-vector.com/2017/09/28/partial-pooling-for-lower-variance-variable-encoding/">https://win-vector.com/2017/09/28/partial-pooling-for-lower-variance-variable-encoding/</a>.

A 'data.frame' processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner.
'vtreat' prepares variables so that data has fewer exceptional cases, making
it easier to safely use models in production. Common problems 'vtreat' defends
against: 'Inf', 'NA', too many categorical levels, rare categorical levels, and new
categorical levels (levels seen during application, but not during training). Reference:
"'vtreat': a data.frame Processor for Predictive Modeling", Zumel, Mount, 2016, <DOI:10.5281/zenodo.1173313>.

John Mount

vtreat

A Statistically Sound 'data.frame' Processor/Conditioner

Nina Zumel

 Win-Vector LLC

ppCoderN function

<dl><dt>v</dt>
<dd>character variable name</dd>
<dt>vcol</dt>
<dd>character, independent or input variable</dd>
<dt>y</dt>
<dd>numeric, dependent or outcome variable to predict</dd>
<dt>w</dt>
<dd>row/example weights</dd></dl>

Arguments

Please see <a href='https://win-vector.com/2017/09/25/custom-level-coding-in-vtreat/'>https://win-vector.com/2017/09/25/custom-level-coding-in-vtreat/</a> and
<a href='https://win-vector.com/2017/09/28/partial-pooling-for-lower-variance-variable-encoding/'>https://win-vector.com/2017/09/28/partial-pooling-for-lower-variance-variable-encoding/</a>.

Solve a numeric partial pooling problem. — ppCoderN

<dl>

<dt>v</dt>
<dd>character variable name</dd>


<dt>vcol</dt>
<dd>character, independent or input variable</dd>


<dt>y</dt>
<dd>numeric, dependent or outcome variable to predict</dd>


<dt>w</dt>
<dd>row/example weights</dd>

</dl>

ppCoderN: Solve a numeric partial pooling problem.

Description

Usage

Value

Arguments