predict.linear.logic

Use new input data and a fitted <code>linear.logic</code> model to
predict corresponding outcomes.

A statistical learning method that tries to find the best set
of predictors and interactions between predictors for modeling binary or
quantitative response data in a decision tree. Several search algorithms
and ensembling techniques are implemented allowing for finetuning the
method to the specific problem. Interactions with quantitative
covariables can be properly taken into account by fitting local
regression models. Moreover, a variable importance measure for assessing
marginal and interaction effects is provided. Implements the
procedures proposed by Lau et al. (2024, <doi:10.1007/s10994-023-06488-6>).

Michael Lau

logicDT

Identifying Interactions Between Binary Predictors

predict.linear.logic function

<dl><dt>object</dt>
<dd>Fitted <code>linear.logic</code> model</dd>
<dt>X</dt>
<dd>Matrix or data frame of binary input data.
This object should correspond to the binary matrix for fitting the model.</dd>
<dt>Z</dt>
<dd>Optional quantitative covariables supplied as a matrix or
data frame. Only used (and required) if the model was fitted using them.</dd>
<dt>s</dt>
<dd>Regularization parameter. Only used if <code>type = "lasso"</code> or
<code>type = "cv.lasso"</code> was set. Only useful if the penalty saved in
<code>object$s</code> should be overwritten.</dd>
<dt>...</dt>
<dd>Ignored additional parameters</dd></dl>

Arguments

Prediction for linear.logic models — predict.linear.logic

<dl>

<dt>object</dt>
<dd>Fitted <code>linear.logic</code> model</dd>


<dt>X</dt>
<dd>Matrix or data frame of binary input data.
This object should correspond to the binary matrix for fitting the model.</dd>


<dt>Z</dt>
<dd>Optional quantitative covariables supplied as a matrix or
data frame. Only used (and required) if the model was fitted using them.</dd>


<dt>s</dt>
<dd>Regularization parameter. Only used if <code>type = "lasso"</code> or
<code>type = "cv.lasso"</code> was set. Only useful if the penalty saved in
<code>object$s</code> should be overwritten.</dd>


<dt>...</dt>
<dd>Ignored additional parameters</dd>

</dl>

predict.linear.logic: Prediction for `linear.logic` models

Description

Usage

Value

Arguments