glicko2_ranking

This procedure ranks algorithms based on a glicko2-procedure.
Every round (total nr_rounds), for every function and dimension of the datasetlist,
each pair of algorithms competes. This competition samples a random runtime for the
provided target (defaults to best achieved target). Whichever algorithm has the lower
runtime wins the game. Then, from these games, the glicko2-rating is determined.

The data analysis module for the Iterative Optimization Heuristics
Profiler ('IOHprofiler'). This module provides statistical analysis methods for the
benchmark data generated by optimization heuristics, which can be visualized through a
web-based interface. The benchmark data is usually generated by the
experimentation module, called 'IOHexperimenter'. 'IOHanalyzer' also supports
the widely used 'COCO' (Comparing Continuous Optimisers) data format for benchmarking.

Diederick Vermetten

IOHanalyzer

Data Analysis Part of 'IOHprofiler'

Hao Wang

Carola Doerr

Thomas Bäck

glicko2_ranking function

<dl><dt>dsl</dt>
<dd>The DataSetList, can contain multiple functions and dimensions, but should have the
same algorithms for all of them</dd>
<dt>nr_rounds</dt>
<dd>The number of rounds to run. More rounds leads to a more accurate ranking.</dd>
<dt>which</dt>
<dd>Whether to use fixed-target ('by_FV') or fixed-budget ('by_RT') perspective</dd>
<dt>target_dt</dt>
<dd>Custom data.table target value to use. When NULL, this is selected automatically.</dd></dl>

Arguments

Glicko2 raning of algorithms — glicko2_ranking

<dl>

<dt>dsl</dt>
<dd>The DataSetList, can contain multiple functions and dimensions, but should have the
same algorithms for all of them</dd>


<dt>nr_rounds</dt>
<dd>The number of rounds to run. More rounds leads to a more accurate ranking.</dd>


<dt>which</dt>
<dd>Whether to use fixed-target ('by_FV') or fixed-budget ('by_RT') perspective</dd>


<dt>target_dt</dt>
<dd>Custom data.table target value to use. When NULL, this is selected automatically.</dd>

</dl>

glicko2_ranking: Glicko2 raning of algorithms

Description

Usage

Value

Arguments

Examples