The Evolutionary Pre-Processor (version 3.0) Batch Run Report |
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Batch Details
Batch run name | concentric_1 |
Description | Concentric 1 on Kaiser |
This report file | final/concentric_1/concentric_1_report.html |
data file | /home/cssip_a/jsherrah/data/concentric_1.dat |
Time of completion | Wed Jun 3 14:20:09 1998 |
Duration of Batch | 14 hours, 29 minutes, 32 seconds |
Random Seed | 671744010 (from clock) |
Average generations per run | 46.30 |
Average failed feature creations per run | 469.50 |
Average fitness evalutions per run | 195926.30 |
Test Set Improvement | 23.52 % |
Data Partition
Class | Training | Validation | Test | Total |
0 | 460 | 230 | 231 | 921 |
1 | 790 | 395 | 394 | 1579 |
Total | 1250 | 625 | 625 | 2500 |
Summary of Results
Original Classification Errors (%)
Classifier | Training | Validation | Test |
Parallelepiped(PPD) | 21.68 | 22.08 | 23.52 |
Min. Distance to Means(MDTM) | 47.04 | 51.20 | 49.92 |
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1 | 0.00 | 0.16 | 0.00 | 1.000 | 1 | 2 | 15 | PPD |
2 | 0.80 | 1.44 | 2.88 | 1.000 | 2 | 2 | 152 | PPD |
3 | 1.12 | 0.80 | 1.92 | 1.000 | 2 | 2 | 100 | PPD |
4 | 1.68 | 1.60 | 3.04 | 1.000 | 2 | 2 | 306 | PPD |
5 | 1.76 | 1.92 | 3.52 | 1.000 | 2 | 2 | 98 | PPD |
6 | 2.16 | 1.28 | 3.04 | 1.000 | 2 | 2 | 20 | PPD |
7 | 1.20 | 0.64 | 1.92 | 1.000 | 2 | 2 | 188 | PPD |
8 | 1.60 | 1.92 | 2.88 | 1.000 | 2 | 2 | 102 | PPD |
9 | 1.60 | 0.48 | 3.52 | 1.000 | 2 | 2 | 88 | PPD |
10 | 0.40 | 1.12 | 2.40 | 1.000 | 2 | 2 | 82 | PPD |
Ave. | 1.23 (0.63 ) | 1.14 (0.57 ) | 2.51 (0.99 ) | 1.00 (0.00 ) | 1.90 (0.30 ) | 2.00 (0.00 ) | 115.10(80.44 ) | PPD |
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Total | ||
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Ground Truth |
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231 | 0 | 231 |
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0 | 394 | 394 | |
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231 | 394 | 625 |
Average Operator Probabilities
Operator | Average Probability |
Delete-Feature Mutation | 0.084 |
Add-Feature Mutation | 0.112 |
Hoist Mutation | 0.092 |
Truncate Mutation | 0.094 |
Swap Mutation | 0.096 |
One-Symbol Mutation | 0.090 |
All-Nodes Mutation | 0.085 |
One-Node Mutation | 0.100 |
Grow Mutation | 0.109 |
High-Level Crossover | 0.138 |
Number of Run Terminations attributed to each Criterion
Termination Criterion | Number of Terminations |
TP Criterion | 0 |
GL Criterion | 2 |
Max. Generations | 8 |
Client Abort | 0 |
Zero Validation Error | 0 |
Total | 10 |
Related Data Files
Description | Filename |
concentric_1_gen.m | Matlab plot generation function |
concentric_1_bogf_ave.{eps,gif} | Best-of-generation Fitness, averaged over 10 runs |
concentric_1_bogv_ave.{eps,gif} | Best-of-generation Validation Set Error, averaged over 10 runs |
concentric_1_avef_ave.{eps,gif} | Average fitness, averaged over 10 runs |
concentric_1_stdf_ave.{eps,gif} | Standard deviation of fitness, averaged over 10 runs |
concentric_1_nftr_ave.{eps,gif} | Average number of features per individual, averaged over 10 runs |
concentric_1_nnode_ave.{eps,gif} | Average number of nodes per individual, averaged over 10 runs |
concentric_1_nint_ave.{eps,gif} | Average number of introns per individual, averaged over 10 runs |
concentric_1_ntrl_ave.{eps,gif} | Average number of RAT trials per individual, averaged over 10 runs |
concentric_1_optimp_ave.{eps,gif} | Average improvement in fitness due to optimisation, averaged over 10 runs |
concentric_1_opprob_ave.{eps,gif} | Average probability of each genetic operator, averaged over 10 runs |
concentric_1_run_x.dat | Binary data file containing results of run x (read by Matlab functions) |
concentric_1_bor_x.prep x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-run individual for run x |
concentric_1_run_x.corr x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Feature correlation file for run x |
concentric_1_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_1_bogf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-generation Fitness for run x |
concentric_1_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_1_avef_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average fitness for run x |
concentric_1_stdf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Standard deviation of fitness for run x |
concentric_1_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_1_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_1_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_1_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_1_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_1_opprob_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average probability of each genetic operator for run x |