confusion_results

Provides a binary confusion table and error metrics

Provides very fast logistic regression with coefficient inferences plus other useful methods such as a forward stepwise model generator (see the benchmarks by visiting the github page at the URL below). The inputs are flexible enough to accomodate GPU computations. The coefficient estimation employs the fastLR() method in the 'RcppNumerical' package by Yixuan Qiu et al. This package allows their work to be more useful to a wider community that consumes inference.

Adam Kapelner

fastLogisticRegressionWrap

Fast Logistic Regression Wrapper

Beau Walker

Gabriel Mayer

confusion_results function

<dl><dt>yhat</dt>
<dd>The binary predictions</dd>
<dt>ybin</dt>
<dd>The true binary responses</dd>
<dt>skip_argument_checks</dt>
<dd>If <code>TRUE</code> it does not check this function's arguments for appropriateness. It is not recommended unless you truly need speed and thus the default is <code>FALSE</code>.</dd></dl>

Arguments

Binary Confusion Table and Errors — confusion_results

<dl>

<dt>yhat</dt>
<dd>The binary predictions</dd>


<dt>ybin</dt>
<dd>The true binary responses</dd>


<dt>skip_argument_checks</dt>
<dd>If <code>TRUE</code> it does not check this function's arguments for appropriateness. It is not recommended unless you truly need speed and thus the default is <code>FALSE</code>.</dd>

</dl>

confusion_results: Binary Confusion Table and Errors

Description

Usage

Value

Arguments

Examples