generate_cv_plot

This function generates a cross-validation plot based on evaluation metrics.

internal

A user-friendly 'shiny' application for Bayesian machine
learning analysis of marine species distributions. GLOSSA (Global
Species Spatiotemporal Analysis) uses Bayesian Additive Regression
Trees (BART; Chipman, George, and McCulloch (2010)
<doi:10.1214/09-AOAS285>) to model species distributions with
intuitive workflows for data upload, processing, model fitting, and
result visualization. It supports presence-absence and presence-only
data (with pseudo-absence generation), spatial thinning,
cross-validation, and scenario-based projections. GLOSSA is designed
to facilitate ecological research by providing easy-to-use tools for
analyzing and visualizing marine species distributions across
different spatial and temporal scales.

Jorge Mestre-Tomás

glossa

User-Friendly 'shiny' App for Bayesian Species Distribution
Models

Alba Fuster-Alonso

generate_cv_plot function

<dl><dt>data</dt>
<dd>Dataframe containing cross-validation results.</dd></dl>

Arguments

Generate Cross-Validation Plot — generate_cv_plot

<dl>

<dt>data</dt>
<dd>Dataframe containing cross-validation results.</dd>

</dl>

generate_cv_plot: Generate Cross-Validation Plot

Description

Usage

Value

Arguments