discretize_get_bins

It takes a data frame and returns another data frame indicating the threshold for each bin (or segment)
in order to discretize the variable.

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.

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Exploratory Data Analysis and Data Preparation Tool-Box

discretize_get_bins function

<dl><dt>data</dt>
<dd>Data frame source</dd>
<dt>n_bins</dt>
<dd>The number of desired bins (or segments) that each variable will have.</dd>
<dt>input</dt>
<dd>Vector of string containing all the variables that will be processed.
If empty it will run for all numerical variables that match the following condition, the number of unique values
must be higher than the ones defined at 'n_bins' parameter. NAs values are automatically handled by converting
them into another category (more info about it at
<a href="https://livebook.datascienceheroes.com/data-preparation.html#treating-missing-values-in-numerical-variables">https://livebook.datascienceheroes.com/data-preparation.html#treating-missing-values-in-numerical-variables</a>).
This function must be used with discretize_df.
If it is needed a different number of bins per variable, then the function must be called more than once.</dd></dl>

Arguments

Get the data frame thresholds for discretization — discretize_get_bins

<dl>

<dt>data</dt>
<dd>Data frame source</dd>


<dt>n_bins</dt>
<dd>The number of desired bins (or segments) that each variable will have.</dd>


<dt>input</dt>
<dd>Vector of string containing all the variables that will be processed.
If empty it will run for all numerical variables that match the following condition, the number of unique values
must be higher than the ones defined at 'n_bins' parameter. NAs values are automatically handled by converting
them into another category (more info about it at
<a href='https://livebook.datascienceheroes.com/data-preparation.html#treating-missing-values-in-numerical-variables'>https://livebook.datascienceheroes.com/data-preparation.html#treating-missing-values-in-numerical-variables</a>).
This function must be used with discretize_df.
If it is needed a different number of bins per variable, then the function must be called more than once.</dd>

</dl>

discretize_get_bins: Get the data frame thresholds for discretization

Description

Usage

Value

Arguments