classify_distribution

<p>Choosing the right distributional family for regression models is essential
to get more accurate estimates and standard errors. This function may help to
Machine learning model trained to classify distributions</p>

datasets

Utilities for computing measures to assess model quality,
which are not directly provided by R's 'base' or 'stats' packages.
These include e.g. measures like r-squared, intraclass correlation
coefficient (Nakagawa, Johnson & Schielzeth (2017)
<doi:10.1098/rsif.2017.0213>), root mean squared error or functions to
check models for overdispersion, singularity or zero-inflation and
more. Functions apply to a large variety of regression models,
including generalized linear models, mixed effects models and Bayesian
models.

Daniel Lüdecke

performance

Assessment of Regression Models Performance

Daniel L<c3><bc>decke

Dominique Makowski

Mattan S. Ben-Shachar

Indrajeet Patil

Philip Waggoner

Brenton M. Wiernik

Vincent Arel-Bundock

Martin Jullum

gjo11 

classify_distribution function

<p>An object of class <code>randomForest.formula</code> (inherits from <code>randomForest</code>) of length 8.</p>

Format

Classify the distribution of a model-family using machine learning — classify_distribution

Classify the distribution of a model-family using machine learning

classify_distribution: Classify the distribution of a model-family using machine learning

Description

Usage

Arguments

Format

Details