The Evolutionary Pre-Processor (version 3.0) Batch Run Report |
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Batch Details
Batch run name | german_1 |
Description | German 1 on Dobson |
This report file | results/final/german_1/german_1_report.html |
data file | /home/users/jsherrah/EPrep3/data/german_1.dat |
Time of completion | Sun Jun 21 03:51:43 1998 |
Duration of Batch | 11 hours, 38 minutes, 28 seconds |
Random Seed | 571123881 (from clock) |
Average generations per run | 42.50 |
Average failed feature creations per run | 6827.60 |
Average fitness evalutions per run | 144253.80 |
Test Set Improvement | 9.60 % |
Data Partition
Class | Training | Validation | Test | Total |
0 | 350 | 175 | 175 | 700 |
1 | 150 | 75 | 75 | 300 |
Total | 500 | 250 | 250 | 1000 |
Summary of Results
Original Classification Errors (%)
Classifier | Training | Validation | Test |
Maximum Likelihood(ML) | 22.00 | 36.00 | 36.40 |
Min. Distance to Means(MDTM) | 37.00 | 36.40 | 40.80 |
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1 | 22.80 | 24.80 | 26.80 | 0.995 | 11 | 10 | 54 | ML |
2 | 27.60 | 26.80 | 28.40 | 0.966 | 3 | 12 | 169 | MDTM |
3 | 17.60 | 28.40 | 32.80 | 0.846 | 18 | 19 | 825 | ML |
4 | 27.40 | 28.80 | 31.20 | 0.889 | 9 | 20 | 929 | MDTM |
5 | 22.00 | 29.20 | 27.60 | 0.999 | 14 | 13 | 20 | ML |
6 | 23.20 | 26.00 | 33.20 | 0.819 | 14 | 15 | 83 | ML |
7 | 21.60 | 28.40 | 29.20 | 0.974 | 12 | 18 | 251 | ML |
8 | 16.40 | 30.00 | 34.00 | 0.788 | 18 | 20 | 355 | ML |
9 | 18.60 | 29.60 | 27.20 | 0.998 | 18 | 19 | 770 | ML |
10 | 23.20 | 27.20 | 26.40 | 1.000 | 14 | 16 | 70 | ML |
Ave. | 22.04 (3.56 ) | 27.92 (1.59 ) | 29.68 (2.73 ) | 0.93 (0.08 ) | 13.10 (4.46 ) | 16.20 (3.40 ) | 352.60(335.56) | ML |
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Total | ||
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Ground Truth |
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147 | 28 | 175 |
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39 | 36 | 75 | |
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186 | 64 | 250 |
Average Operator Probabilities
Operator | Average Probability |
Delete-Feature Mutation | 0.093 |
Add-Feature Mutation | 0.110 |
Hoist Mutation | 0.102 |
Truncate Mutation | 0.096 |
Swap Mutation | 0.103 |
One-Symbol Mutation | 0.099 |
All-Nodes Mutation | 0.098 |
One-Node Mutation | 0.093 |
Grow Mutation | 0.097 |
High-Level Crossover | 0.108 |
Number of Run Terminations attributed to each Criterion
Termination Criterion | Number of Terminations |
TP Criterion | 0 |
GL Criterion | 5 |
Max. Generations | 5 |
Client Abort | 0 |
Zero Validation Error | 0 |
Total | 10 |
Related Data Files
Description | Filename |
german_1_gen.m | Matlab plot generation function |
german_1_bogf_ave.{eps,gif} | Best-of-generation Fitness, averaged over 10 runs |
german_1_bogv_ave.{eps,gif} | Best-of-generation Validation Set Error, averaged over 10 runs |
german_1_avef_ave.{eps,gif} | Average fitness, averaged over 10 runs |
german_1_stdf_ave.{eps,gif} | Standard deviation of fitness, averaged over 10 runs |
german_1_nftr_ave.{eps,gif} | Average number of features per individual, averaged over 10 runs |
german_1_nnode_ave.{eps,gif} | Average number of nodes per individual, averaged over 10 runs |
german_1_nint_ave.{eps,gif} | Average number of introns per individual, averaged over 10 runs |
german_1_ntrl_ave.{eps,gif} | Average number of RAT trials per individual, averaged over 10 runs |
german_1_optimp_ave.{eps,gif} | Average improvement in fitness due to optimisation, averaged over 10 runs |
german_1_opprob_ave.{eps,gif} | Average probability of each genetic operator, averaged over 10 runs |
german_1_run_x.dat | Binary data file containing results of run x (read by Matlab functions) |
german_1_bor_x.prep x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-run individual for run x |
german_1_run_x.corr x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Feature correlation file for run x |
german_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 |
german_1_bogf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-generation Fitness for run x |
german_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 |
german_1_avef_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average fitness for run x |
german_1_stdf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Standard deviation of fitness for run x |
german_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 |
german_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 |
german_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 |
german_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 |
german_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 |
german_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 |