nomogram_outputs

An example of a data frame for <code>sample_output</code> argument in
<code>create_nomogram</code> function, must only include the predicted
probabilities for binary outcome.

dataset

Construct an explainable nomogram for a machine learning (ML) model to improve availability of an ML prediction model in addition to a computer application, particularly in a situation where a computer, a mobile phone, an internet connection, or the application accessibility are unreliable. This package enables a nomogram creation for any ML prediction models, which is conventionally limited to only a linear/logistic regression model. This nomogram may indicate the explainability value per feature, e.g., the Shapley additive explanation value, for each individual. However, this package only allows a nomogram creation for a model using categorical without or with single numerical predictors. Detailed methodologies and examples are documented in our vignette, available at <https://htmlpreview.github.io/?https://github.com/herdiantrisufriyana/rmlnomogram/blob/master/doc/ml_nomogram_exemplar.html>.

Herdiantri Sufriyana

rmlnomogram

Construct Explainable Nomogram for a Machine Learning Model

Emily Chia-Yu Su

nomogram_outputs function

A data frame with 16 rows and 1 column:<dl>
<dt>output</dt>
<dd>A binary outcome with values from 0 to 1.</dd>
</dl>

Format

Nomogram outputs using the predicted probability of binary outcome — nomogram_outputs

A data frame with 16 rows and 1 column:<dl>
<dt>output</dt>
<dd>A binary outcome with values from 0 to 1.</dd>


</dl>

nomogram_outputs: Nomogram outputs using the predicted probability of binary outcome

Description

Usage

Arguments

Format