preprocessTestData

data frame with $n$ obs. of 4 variables:<dl class="dl-horizontal">
<dt><code>ForecastId</code></dt><dd>int Identifier 1 2 3 ...</dd> 
<dt><code>Province_State</code></dt><dd>chr Province/State</dd> 
<dt><code>Country_Region</code></dt><dd>chr Country/Region, e.g., "Afghanistan" ...</dd> 
<dt><code>Date</code></dt><dd>Date, format: "2020-04-02" ...</dd> 
</dl>

testData

Combine Province/State and Country/Region information.

A set of tools for model-based optimization and tuning of
algorithms. It includes surrogate models, optimizers, and design of experiment
approaches. The main interface is spot, which uses sequentially updated
surrogate models for the purpose of efficient optimization. The main goal is
to ease the burden of objective function evaluations, when a single evaluation
requires a significant amount of resources.

Thomas Bartz-Beielstein

SPOT

Sequential Parameter Optimization Toolbox

Joerg Stork

Martin Zaefferer

Margarita Rebolledo

Christian Lasarczyk

Frederik Rehbach

preprocessTestData function

data frame with $n$ obs. of 4 variables:<dl class='dl-horizontal'>
<dt><code>ForecastId</code></dt><dd>int Identifier 1 2 3 ...</dd> 
<dt><code>Province_State</code></dt><dd>chr Province/State</dd> 
<dt><code>Country_Region</code></dt><dd>chr Country/Region, e.g., "Afghanistan" ...</dd> 
<dt><code>Date</code></dt><dd>Date, format: "2020-04-02" ...</dd> 
</dl>

preprocessTestData: preprocessTestData

Description

Usage

Arguments

Value

Details

Examples