ph_iqr

The <code>ph_iqr</code> function computes the interquartile range.

A system for binary and multi-class classification of
high-dimensional phenotypic data using ensemble learning. By combining
predictions from different classification models, this package attempts
to improve performance over individual learners. The pre-processing,
training, validation, and testing are performed end-to-end to minimize
user input and simplify the process of classification.

Jay Devine

pheble

Classifying High-Dimensional Phenotypes with Ensemble Learning

Bened'ikt Hallgrimsson

ph_iqr function

<dl><dt>x</dt>
<dd>A <code>numeric</code> vector.</dd>
<dt>na.rm</dt>
<dd>A <code>logical</code> value: FALSE (default). If true, any NA is removed before quantiles are computed.</dd>
<dt>type</dt>
<dd>An <code>integer</code> value (1:9) selecting one of 9 quantile algorithms.</dd></dl>

Arguments

Compute interquartile range. — ph_iqr

<dl>

<dt>x</dt>
<dd>A <code>numeric</code> vector.</dd>


<dt>na.rm</dt>
<dd>A <code>logical</code> value: FALSE (default). If true, any NA is removed before quantiles are computed.</dd>


<dt>type</dt>
<dd>An <code>integer</code> value (1:9) selecting one of 9 quantile algorithms.</dd>

</dl>

ph_iqr: Compute interquartile range.

Description

Usage

Value

Arguments