linScore

varName

numeric vector of inputs (no NA/NULL/NaN)

xcol

numeric vector of outcomes (no NA/NULL/NaN)

ycol

numeric vector of data weights (no NA/NULL/NaN, all&gt;0.0)

weights

optional scalar &gt;= 0 number of additional modeling degrees of freedom to account for.

numberOfHiddenDegrees

Return in-sample linear stats and scaling.

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.1173314.

linScore: Return in-sample linear stats and scaling.

Description

Usage

Arguments

Value