is_degree

Tests whether the given argument is a numeric value from the interval
\([0,1]\)

Extensible framework for
subgroup discovery (Atzmueller (2015) <doi:10.1002/widm.1144>),
contrast patterns (Chen (2022) <doi:10.48550/arXiv.2209.13556>),
emerging patterns (Dong (1999) <doi:10.1145/312129.312191>),
association rules (Agrawal (1994) <https://www.vldb.org/conf/1994/P487.PDF>) and
conditional correlations (Hájek (1978) <doi:10.1007/978-3-642-66943-9>).
Both crisp (Boolean, binary) and fuzzy data are supported.
It generates conditions in the form of elementary conjunctions, evaluates
them on a dataset and checks the induced sub-data for interesting statistical
properties. A user-defined function may be defined to evaluate on each generated
condition to search for custom patterns.

Michal Burda

nuggets

Extensible Data Pattern Searching Framework

is_degree function

<dl><dt>x</dt>
<dd>the value to be tested</dd>
<dt>na_rm</dt>
<dd>whether to ignore <code>NA</code> values</dd></dl>

Arguments

Author

Tests whether the given argument is a numeric value from the interval
\([0,1]\) — is_degree

<dl>

<dt>x</dt>
<dd>the value to be tested</dd>


<dt>na_rm</dt>
<dd>whether to ignore <code>NA</code> values</dd>

</dl>

is_degree: Tests whether the given argument is a numeric value from the interval \([0,1]\)

Description

Usage

Value

Arguments

Author