infor_magic

It retrieves the same as <code>var_rank_info</code> but receiving two vectors.
Metrics are: entropy (en), mutual information (mi), information gain (ig) and gain ratio (gr).

Around 10% of almost any predictive modeling project is spent in predictive modeling, 'funModeling' and the book Data Science Live Book (<https://livebook.datascienceheroes.com/>) are intended to cover remaining 90%: data preparation, profiling, selecting best variables 'dataViz', assessing model performance and other functions.

Pablo Casas

funModeling

Exploratory Data Analysis and Data Preparation Tool-Box

infor_magic function

<dl><dt>input</dt>
<dd>vector to be evaluated against the variable defined in 'target' parameter</dd>
<dt>target</dt>
<dd>vector containing the output variable.</dd></dl>

Arguments

Computes several information theory metrics between two vectors — infor_magic

<dl>

<dt>input</dt>
<dd>vector to be evaluated against the variable defined in 'target' parameter</dd>


<dt>target</dt>
<dd>vector containing the output variable.</dd>

</dl>

infor_magic: Computes several information theory metrics between two vectors

Description

Usage

Value

Arguments

Examples