The Evolutionary Pre-Processor (version 3.0) Batch Run Report |
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Batch Details
Batch run name | concentric_2 |
Description | Concentric 2 on Android |
This report file | final/concentric_2/concentric_2_report.html |
data file | /home/cssip_a/jsherrah/data/concentric_2.dat |
Time of completion | Thu Jun 4 16:05:30 1998 |
Duration of Batch | 25 hours, 40 minutes, 46 seconds |
Random Seed | 2192048160 (from clock) |
Average generations per run | 43.10 |
Average failed feature creations per run | 453.20 |
Average fitness evalutions per run | 252526.90 |
Test Set Improvement | 20.96 % |
Data Partition
Class | Training | Validation | Test | Total |
0 | 460 | 231 | 230 | 921 |
1 | 790 | 394 | 395 | 1579 |
Total | 1250 | 625 | 625 | 2500 |
Summary of Results
Original Classification Errors (%)
Classifier | Training | Validation | Test |
Parallelepiped(PPD) | 23.28 | 21.44 | 22.88 |
Min. Distance to Means(MDTM) | 48.64 | 50.72 | 51.04 |
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1 | 0.96 | 1.28 | 2.08 | 1.000 | 2 | 2 | 90 | PPD |
2 | 0.64 | 1.60 | 2.24 | 1.000 | 2 | 2 | 254 | PPD |
3 | 1.68 | 1.92 | 3.36 | 1.000 | 2 | 2 | 70 | PPD |
4 | 0.80 | 0.48 | 1.92 | 1.000 | 2 | 2 | 92 | PPD |
5 | 1.60 | 2.88 | 2.56 | 1.000 | 2 | 2 | 62 | PPD |
6 | 2.08 | 1.76 | 3.20 | 1.000 | 2 | 2 | 46 | PPD |
7 | 0.40 | 0.80 | 0.96 | 1.000 | 2 | 2 | 30 | PPD |
8 | 1.76 | 1.44 | 2.72 | 1.000 | 2 | 2 | 18 | PPD |
9 | 2.08 | 2.40 | 1.92 | 1.000 | 2 | 2 | 120 | PPD |
10 | 0.40 | 0.64 | 1.28 | 1.000 | 2 | 2 | 50 | PPD |
Ave. | 1.24 (0.64 ) | 1.52 (0.73 ) | 2.22 (0.73 ) | 1.00 (0.00 ) | 2.00 (0.00 ) | 2.00 (0.00 ) | 83.20 (63.91 ) | PPD |
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Total | ||
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Ground Truth |
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227 | 3 | 230 |
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9 | 386 | 395 | |
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236 | 389 | 625 |
Average Operator Probabilities
Operator | Average Probability |
Delete-Feature Mutation | 0.084 |
Add-Feature Mutation | 0.091 |
Hoist Mutation | 0.083 |
Truncate Mutation | 0.103 |
Swap Mutation | 0.121 |
One-Symbol Mutation | 0.095 |
All-Nodes Mutation | 0.092 |
One-Node Mutation | 0.093 |
Grow Mutation | 0.100 |
High-Level Crossover | 0.139 |
Number of Run Terminations attributed to each Criterion
Termination Criterion | Number of Terminations |
TP Criterion | 1 |
GL Criterion | 3 |
Max. Generations | 6 |
Client Abort | 0 |
Zero Validation Error | 0 |
Total | 10 |
Related Data Files
Description | Filename |
concentric_2_gen.m | Matlab plot generation function |
concentric_2_bogf_ave.{eps,gif} | Best-of-generation Fitness, averaged over 10 runs |
concentric_2_bogv_ave.{eps,gif} | Best-of-generation Validation Set Error, averaged over 10 runs |
concentric_2_avef_ave.{eps,gif} | Average fitness, averaged over 10 runs |
concentric_2_stdf_ave.{eps,gif} | Standard deviation of fitness, averaged over 10 runs |
concentric_2_nftr_ave.{eps,gif} | Average number of features per individual, averaged over 10 runs |
concentric_2_nnode_ave.{eps,gif} | Average number of nodes per individual, averaged over 10 runs |
concentric_2_nint_ave.{eps,gif} | Average number of introns per individual, averaged over 10 runs |
concentric_2_ntrl_ave.{eps,gif} | Average number of RAT trials per individual, averaged over 10 runs |
concentric_2_optimp_ave.{eps,gif} | Average improvement in fitness due to optimisation, averaged over 10 runs |
concentric_2_opprob_ave.{eps,gif} | Average probability of each genetic operator, averaged over 10 runs |
concentric_2_run_x.dat | Binary data file containing results of run x (read by Matlab functions) |
concentric_2_bor_x.prep x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-run individual for run x |
concentric_2_run_x.corr x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Feature correlation file for run x |
concentric_2_tst_bor_x.pred x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Test set predictions for best-of-run individual from run x |
concentric_2_bogf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-generation Fitness for run x |
concentric_2_bogv_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-generation Validation Set Error for run x |
concentric_2_avef_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average fitness for run x |
concentric_2_stdf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Standard deviation of fitness for run x |
concentric_2_nftr_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average number of features per individual for run x |
concentric_2_nnode_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average number of nodes per individual for run x |
concentric_2_nint_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average number of introns per individual for run x |
concentric_2_ntrl_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average number of RAT trials per individual for run x |
concentric_2_optimp_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average improvement in fitness due to optimisation for run x |
concentric_2_opprob_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average probability of each genetic operator for run x |