check_predictor_matrix

Performs a number of checks on a custom predictor matrix and returns error if the matrix is
not in a valid format.

Missing data imputation based on the 'missForest' algorithm (Stekhoven, Daniel J (2012) <doi:10.1093/bioinformatics/btr597>)
with adaptations for prediction settings. The function missForest() is used
to impute a (training) dataset with missing values and to learn imputation
models that can be later used for imputing new observations.
The function missForestPredict() is used to impute one or multiple new
observations (test set) using the models learned on the training data.

Elena Albu

missForestPredict

Missing Value Imputation using Random Forest for Prediction
Settings

check_predictor_matrix function

<dl><dt>predictor_matrix</dt>
<dd>custom predictor matrix</dd>
<dt>data</dt>
<dd>dataframe to be imputed</dd>
<dt>verbose</dt>
<dd>if TRUE, returns human readable message for the checks performed.</dd></dl>

Arguments

Performs checks on a custom predictor matrix — check_predictor_matrix

<dl>

<dt>predictor_matrix</dt>
<dd>custom predictor matrix</dd>


<dt>data</dt>
<dd>dataframe to be imputed</dd>


<dt>verbose</dt>
<dd>if TRUE, returns human readable message for the checks performed.</dd>

</dl>

check_predictor_matrix: Performs checks on a custom predictor matrix

Description

Usage

Value

Arguments