bins.quantiles

Cuts the data set x into roughly equal groups using quantiles
Because the number of unique values may be smaller than target.bins,
the function gradually increases the number of quantiles up to max.breaks
or until the target.bins number of bins is reached.

Package binr (pronounced as "binner") provides algorithms for cutting numerical values exhibiting a potentially highly skewed distribution into evenly distributed groups (bins). This functionality can be applied for binning discrete values, such as counts, as well as for discretization of continuous values, for example, during generation of features used in machine learning algorithms.

Sergei Izrailev

binr

Cut Numeric Values into Evenly Distributed Groups

bins.quantiles function

<dl><dt>x</dt>
<dd>A numeric vector to be cut in bins.</dd>
<dt>target.bins</dt>
<dd>Target number of bins, which may not be reached if the
number of unique values is smaller than the specified value.</dd>
<dt>max.breaks</dt>
<dd>Maximum number of quantiles; must be at least as
large as <code>target.bins</code>.</dd>
<dt>verbose</dt>
<dd>Indicates verbose output.</dd></dl>

Arguments

Quantile-based binning — bins.quantiles

<dl>

<dt>x</dt>
<dd>A numeric vector to be cut in bins.</dd>


<dt>target.bins</dt>
<dd>Target number of bins, which may not be reached if the
number of unique values is smaller than the specified value.</dd>


<dt>max.breaks</dt>
<dd>Maximum number of quantiles; must be at least as
large as <code>target.bins</code>.</dd>


<dt>verbose</dt>
<dd>Indicates verbose output.</dd>

</dl>

bins.quantiles: Quantile-based binning

Description

Usage

Arguments

See Also