bins.merr

Partitioning the data into bins using splitting, merging
and moving optimizes this error function, which is the mean squared error
of point counts in the bins relative to the optimal number of points per bin.

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.merr function

<dl><dt>binct</dt>
<dd>The number of points falling into the bins.</dd>
<dt>target.bins</dt>
<dd>Number of bins desired; this is also the max number of bins.</dd></dl>

Arguments

Binning Error Function — bins.merr

<dl>

<dt>binct</dt>
<dd>The number of points falling into the bins.</dd>


<dt>target.bins</dt>
<dd>Number of bins desired; this is also the max number of bins.</dd>

</dl>

bins.merr: Binning Error Function

Description

Usage

Value

Arguments

See Also