normalize

Standardize the columns of an attribute matrix <code>X</code> to zscores, to the
range <code>[0 1]</code> or a prespecified scale.

Implements the SVM-Maj algorithm to train data with support vector machine
<doi:10.1007/s11634-008-0020-9>.
This algorithm uses two efficient updates, one for linear kernel and one
for the nonlinear kernel.

Hok San Yip

SVMMaj

Implementation of the SVM-Maj Algorithm

Hoksan Yip

Georgi Nalbantov

normalize function

<dl><dt>x</dt>
<dd>An attribute variable which will be scaled.</dd>
<dt>standardize</dt>
<dd>Either a string value denoting a predefined scaling, or a
list with values <code>a</code> and <code>b</code> corresponding with the numeric
centering and scaling, that is, using the function <code>x * standardize$b -
standardize$a</code>.</dd></dl>

Arguments

Hok San Yip, Patrick J.F. Groenen, Georgi Nalbantov

Author

Normalize/standardize the columns of a matrix — normalize

<dl>

<dt>x</dt>
<dd>An attribute variable which will be scaled.</dd>


<dt>standardize</dt>
<dd>Either a string value denoting a predefined scaling, or a
list with values <code>a</code> and <code>b</code> corresponding with the numeric
centering and scaling, that is, using the function <code>x * standardize$b -
standardize$a</code>.</dd>

</dl>

normalize: Normalize/standardize the columns of a matrix

Description

Usage

Value

Arguments

Author

References

See Also

Examples