The Evolutionary Pre-Processor (version 3.0) Batch Run Report |
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Batch Details
Batch run name | spirals_3 |
Description | Spirals 3 on Kaiser |
This report file | spirals_3/spirals_3_report.html |
data file | /home/cssip/jsherrah/EPrep3/data/spirals_3.dat |
Time of completion | Sat Jun 20 22:03:39 1998 |
Duration of Batch | 6 hours, 13 minutes, 14 seconds |
Random Seed | 2726987811 (from clock) |
Average generations per run | 51.30 |
Average failed feature creations per run | 526.10 |
Average fitness evalutions per run | 450262.40 |
Test Set Improvement | 19.21 % |
Data Partition
Class | Training | Validation | Test | Total |
0 | 100 | 45 | 240 | 385 |
1 | 94 | 52 | 239 | 385 |
Total | 194 | 97 | 479 | 770 |
Summary of Results
Original Classification Errors (%)
Classifier | Training | Validation | Test |
Maximum Likelihood(ML) | 44.33 | 49.48 | 51.15 |
Parallelepiped(PPD) | 44.33 | 46.39 | 51.57 |
Min. Distance to Means(MDTM) | 44.85 | 45.36 | 51.36 |
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1 | 18.56 | 19.59 | 32.15 | 1.000 | 2 | 2 | 101 | ML |
2 | 21.13 | 29.90 | 27.14 | 1.000 | 2 | 2 | 48 | ML |
3 | 17.53 | 27.84 | 24.01 | 1.000 | 2 | 2 | 21 | ML |
4 | 20.62 | 30.93 | 30.27 | 1.000 | 2 | 2 | 70 | ML |
5 | 23.71 | 32.99 | 28.81 | 1.000 | 2 | 2 | 30 | ML |
6 | 20.62 | 25.77 | 20.46 | 1.000 | 2 | 2 | 25 | ML |
7 | 31.44 | 34.02 | 36.33 | 1.000 | 2 | 2 | 33 | ML |
8 | 21.65 | 31.96 | 37.16 | 1.000 | 2 | 2 | 10 | ML |
9 | 35.05 | 35.05 | 30.48 | 1.000 | 1 | 1 | 14 | ML |
10 | 15.98 | 28.87 | 28.39 | 1.000 | 2 | 2 | 24 | ML |
Ave. | 22.63 (5.76 ) | 29.69 (4.32 ) | 29.52 (4.83 ) | 1.00 (0.00 ) | 1.90 (0.30 ) | 1.90 (0.30 ) | 37.60 (26.82 ) | ML |
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Total | ||
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Ground Truth |
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158 | 82 | 240 |
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72 | 167 | 239 | |
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230 | 249 | 479 |
Average Operator Probabilities
Operator | Average Probability |
Delete-Feature Mutation | 0.072 |
Add-Feature Mutation | 0.092 |
Hoist Mutation | 0.078 |
Truncate Mutation | 0.107 |
Swap Mutation | 0.127 |
One-Symbol Mutation | 0.092 |
All-Nodes Mutation | 0.080 |
One-Node Mutation | 0.097 |
Grow Mutation | 0.103 |
High-Level Crossover | 0.152 |
Number of Run Terminations attributed to each Criterion
Termination Criterion | Number of Terminations |
TP Criterion | 10 |
GL Criterion | 0 |
Max. Generations | 0 |
Client Abort | 0 |
Zero Validation Error | 0 |
Total | 10 |
Related Data Files
Description | Filename |
spirals_3_gen.m | Matlab plot generation function |
spirals_3_bogf_ave.{eps,gif} | Best-of-generation Fitness, averaged over 10 runs |
spirals_3_bogv_ave.{eps,gif} | Best-of-generation Validation Set Error, averaged over 10 runs |
spirals_3_avef_ave.{eps,gif} | Average fitness, averaged over 10 runs |
spirals_3_stdf_ave.{eps,gif} | Standard deviation of fitness, averaged over 10 runs |
spirals_3_nftr_ave.{eps,gif} | Average number of features per individual, averaged over 10 runs |
spirals_3_nnode_ave.{eps,gif} | Average number of nodes per individual, averaged over 10 runs |
spirals_3_nint_ave.{eps,gif} | Average number of introns per individual, averaged over 10 runs |
spirals_3_ntrl_ave.{eps,gif} | Average number of RAT trials per individual, averaged over 10 runs |
spirals_3_optimp_ave.{eps,gif} | Average improvement in fitness due to optimisation, averaged over 10 runs |
spirals_3_opprob_ave.{eps,gif} | Average probability of each genetic operator, averaged over 10 runs |
spirals_3_run_x.dat | Binary data file containing results of run x (read by Matlab functions) |
spirals_3_bor_x.prep x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-run individual for run x |
spirals_3_run_x.corr x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Feature correlation file for run x |
spirals_3_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 |
spirals_3_bogf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-generation Fitness for run x |
spirals_3_bogv_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-generation Validation Set Error for run x |
spirals_3_avef_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average fitness for run x |
spirals_3_stdf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Standard deviation of fitness for run x |
spirals_3_nftr_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average number of features per individual for run x |
spirals_3_nnode_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average number of nodes per individual for run x |
spirals_3_nint_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average number of introns per individual for run x |
spirals_3_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 |
spirals_3_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 |
spirals_3_opprob_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average probability of each genetic operator for run x |