problemAppPlan

check if appPlan is a good carve-up of 1:nRows into nSplits groups

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

problemAppPlan function

<dl><dt>nRows</dt>
<dd>number of rows to carve-up</dd>
<dt>nSplits</dt>
<dd>number of sets to carve-up into</dd>
<dt>appPlan</dt>
<dd>carve-up to critique</dd>
<dt>strictCheck</dt>
<dd>logical, if true expect application data to be a carve-up and training data to be a maximal partition and to match nSplits.</dd></dl>

Arguments

check if appPlan is a good carve-up of 1:nRows into nSplits groups — problemAppPlan

<dl>

<dt>nRows</dt>
<dd>number of rows to carve-up</dd>


<dt>nSplits</dt>
<dd>number of sets to carve-up into</dd>


<dt>appPlan</dt>
<dd>carve-up to critique</dd>


<dt>strictCheck</dt>
<dd>logical, if true expect application data to be a carve-up and training data to be a maximal partition and to match nSplits.</dd>

</dl>

problemAppPlan: check if appPlan is a good carve-up of 1:nRows into nSplits groups

Description

Usage

Value

Arguments

See Also

Examples