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Tuned SHC.xlsx (14.84 MB)
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Untuned BA.xlsx (14.98 MB)
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Untuned BFOA.xlsx (14.81 MB)
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Untuned GA.xlsx (13.8 MB)
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Untuned ES.xlsx (15.01 MB)
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Untuned PSO.xlsx (14.99 MB)
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Untuned SHC.xlsx (14.56 MB)
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Tuned HS.xlsx (15.02 MB)
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Summary.xlsx (50.39 kB)
DATASET
Tuned GA.xlsx (15 MB)
DATASET
Tuned HS.xlsx (15.02 MB)
DATASET
Tuned ES.xlsx (15.01 MB)
DATASET
Tuned ES.xlsx (15.01 MB)
DATASET
Tuned BFOA.xlsx (14.99 MB)
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Tuned GA.xlsx (15 MB)
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Data Set to Accompany "Quantifying the Impact of Parameter Tuning on Nature-Inspired Algorithms"

Version 5 2013-05-22, 11:55
Version 4 2013-05-22, 11:55
dataset
posted on 2013-05-22, 11:55 authored by Matthew CrossleyMatthew Crossley, Andy Nisbet, Martyn AmosMartyn Amos

Performance data gathered in the experiments described in 'Quantifying the Impact of Parameter Tuning on Nature-Inspired Algorithms' (Crossley, Nisbet and Amos (2013)).

 

'Raw' performance data - that is to say, the best fitness from all runs performed - are available in the individual sheets labelled Untuned/Tuned , where performance data is split across 5 sheets - one for each characteristic.

 

Summary.xlsx contains a summary of all the data - average performance/standard deviation for each characteristic value, for each algorithm.

 

Parameters.xlsx contains a summary of the parameters used, both the 'default' (untuned) and tuned parameters selected by the F-Racing process.

 

The accompanying paper has been submitted to the European Conference on Artificial Life 2013 (ECAL13).

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