multivariate_linear_regression

Calculates and plots the linear regression of a given set of values.
Being all of them independent values but one, which is the dependent value.
It provides information about the process and intermediate values used to calculate the line equation.

Supervised classification methods, which (if asked) can provide
step-by-step explanations of the algorithms used, as described in
PK Josephine et. al., (2021) <doi:10.59176/kjcs.v1i1.1259>; and datasets to
test them on, which highlight the strengths and weaknesses of each technique.

Víctor Amador Padilla

LearnSL

Learn Supervised Classification Methods Through Examples and
Code

Juan Jose Cuadrado Gallego

Universidad de Alcala 

multivariate_linear_regression function

<dl><dt>data</dt>
<dd>x*y data frame with already classified observations. Each column
represents a parameter of the values (independent variable). The last column
represents the classification value (dependent variable). Each row is a different observation.</dd>
<dt>details</dt>
<dd>Boolean value. If it is set to "TRUE" multiple clarifications
and explanations are printed along the code</dd>
<dt>waiting</dt>
<dd>If TRUE while <code>details</code> = TRUE. The code will stop in each
"block" of code and wait for the user to press "enter" to continue.</dd></dl>

Arguments

Víctor Amador Padilla, <a href="/link/victor.amador%40edu.uah.es?package=LearnSL&version=1.0.0" data-mini-rdoc="LearnSL::victor.amador@edu.uah.es">victor.amador@edu.uah.es</a>

Author

Multivariate Linear Regression — multivariate_linear_regression

<dl>

<dt>data</dt>
<dd>x*y data frame with already classified observations. Each column
represents a parameter of the values (independent variable). The last column
represents the classification value (dependent variable). Each row is a different observation.</dd>


<dt>details</dt>
<dd>Boolean value. If it is set to "TRUE" multiple clarifications
and explanations are printed along the code</dd>


<dt>waiting</dt>
<dd>If TRUE while <code>details</code> = TRUE. The code will stop in each
"block" of code and wait for the user to press "enter" to continue.</dd>

</dl>

Víctor Amador Padilla, <a href='mailto:victor.amador@edu.uah.es'>victor.amador@edu.uah.es</a>

multivariate_linear_regression: Multivariate Linear Regression

Description

Usage

Value

Arguments

Author

Examples