miMatrix

Attribute table, given as a data frame with either factors (preferred), booleans, integers (treated as categorical) or reals (which undergo automatic categorisation; see below for details).
Single vector will be interpreted as a data.frame with one column.
<code>NA</code>s are not allowed.

Boolean flag, whether the diagonal should be filled with zeroes, or with degenerated scores for two identical copies of a feature.

zeroDiag

Number of threads to use; default value, 0, means all available to OpenMP.

threads

Calculates mutual information between each two features, that is
$$I(X_i,X_j).$$

praznik

miMatrix function

<dl><dt>X</dt>
<dd>Attribute table, given as a data frame with either factors (preferred), booleans, integers (treated as categorical) or reals (which undergo automatic categorisation; see below for details).
Single vector will be interpreted as a data.frame with one column.
<code>NA</code>s are not allowed.</dd>
<dt>zeroDiag</dt>
<dd>Boolean flag, whether the diagonal should be filled with zeroes, or with degenerated scores for two identical copies of a feature.</dd>
<dt>threads</dt>
<dd>Number of threads to use; default value, 0, means all available to OpenMP.</dd></dl>

Arguments

Mutual information matrix — miMatrix

<dl>

<dt>X</dt>
<dd>Attribute table, given as a data frame with either factors (preferred), booleans, integers (treated as categorical) or reals (which undergo automatic categorisation; see below for details).
Single vector will be interpreted as a data.frame with one column.
<code>NA</code>s are not allowed.</dd>


<dt>zeroDiag</dt>
<dd>Boolean flag, whether the diagonal should be filled with zeroes, or with degenerated scores for two identical copies of a feature.</dd>


<dt>threads</dt>
<dd>Number of threads to use; default value, 0, means all available to OpenMP.</dd>

</dl>

miMatrix: Mutual information matrix

Description

Usage

Value

Arguments

Examples