The Evolutionary Pre-Processor (version 3.0) Batch Run Report |
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Batch Details
Batch run name | german_3 |
Description | German 3 on Atlas |
This report file | german_3/german_3_report.html |
data file | /home/cssip/jsherrah/EPrep3/data/german_3.dat |
Time of completion | Sun Jun 21 18:22:58 1998 |
Duration of Batch | 27 hours, 33 minutes, 45 seconds |
Random Seed | 2192058883 (from clock) |
Average generations per run | 29.60 |
Average failed feature creations per run | 6868.00 |
Average fitness evalutions per run | 93901.30 |
Test Set Improvement | 0.80 % |
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) | 26.20 | 32.80 | 29.20 |
Min. Distance to Means(MDTM) | 39.60 | 38.00 | 37.20 |
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1 | 29.00 | 27.60 | 27.60 | 0.652 | 1 | 11 | 283 | MDTM |
2 | 25.80 | 24.80 | 27.20 | 0.716 | 12 | 15 | 138 | ML |
3 | 30.00 | 26.40 | 30.00 | 0.417 | 12 | 16 | 984 | MDTM |
4 | 28.80 | 25.60 | 29.20 | 0.500 | 3 | 11 | 343 | ML |
5 | 27.40 | 24.80 | 26.40 | 0.761 | 11 | 16 | 716 | MDTM |
6 | 20.00 | 23.60 | 24.40 | 0.974 | 17 | 17 | 248 | ML |
7 | 29.80 | 26.00 | 26.40 | 0.831 | 8 | 8 | 19 | ML |
8 | 25.00 | 22.80 | 28.40 | 0.599 | 12 | 19 | 432 | ML |
9 | 27.20 | 24.80 | 28.40 | 0.606 | 11 | 11 | 19 | ML |
10 | 18.00 | 24.80 | 26.80 | 0.782 | 20 | 20 | 881 | ML |
Ave. | 26.10 (3.89 ) | 25.12 (1.30 ) | 27.48 (1.53 ) | 0.68 (0.16 ) | 10.70 (5.40 ) | 14.40 (3.75 ) | 406.30(327.40) | ML |
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Total | ||
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Ground Truth |
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143 | 32 | 175 |
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39 | 36 | 75 | |
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182 | 68 | 250 |
Average Operator Probabilities
Operator | Average Probability |
Delete-Feature Mutation | 0.099 |
Add-Feature Mutation | 0.104 |
Hoist Mutation | 0.109 |
Truncate Mutation | 0.103 |
Swap Mutation | 0.098 |
One-Symbol Mutation | 0.089 |
All-Nodes Mutation | 0.090 |
One-Node Mutation | 0.101 |
Grow Mutation | 0.099 |
High-Level Crossover | 0.109 |
Number of Run Terminations attributed to each Criterion
Termination Criterion | Number of Terminations |
TP Criterion | 0 |
GL Criterion | 9 |
Max. Generations | 1 |
Client Abort | 0 |
Zero Validation Error | 0 |
Total | 10 |
Related Data Files
Description | Filename |
german_3_gen.m | Matlab plot generation function |
german_3_bogf_ave.{eps,gif} | Best-of-generation Fitness, averaged over 10 runs |
german_3_bogv_ave.{eps,gif} | Best-of-generation Validation Set Error, averaged over 10 runs |
german_3_avef_ave.{eps,gif} | Average fitness, averaged over 10 runs |
german_3_stdf_ave.{eps,gif} | Standard deviation of fitness, averaged over 10 runs |
german_3_nftr_ave.{eps,gif} | Average number of features per individual, averaged over 10 runs |
german_3_nnode_ave.{eps,gif} | Average number of nodes per individual, averaged over 10 runs |
german_3_nint_ave.{eps,gif} | Average number of introns per individual, averaged over 10 runs |
german_3_ntrl_ave.{eps,gif} | Average number of RAT trials per individual, averaged over 10 runs |
german_3_optimp_ave.{eps,gif} | Average improvement in fitness due to optimisation, averaged over 10 runs |
german_3_opprob_ave.{eps,gif} | Average probability of each genetic operator, averaged over 10 runs |
german_3_run_x.dat | Binary data file containing results of run x (read by Matlab functions) |
german_3_bor_x.prep x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-run individual for run x |
german_3_run_x.corr x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Feature correlation file for run x |
german_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 |
german_3_bogf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-generation Fitness for run x |
german_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 |
german_3_avef_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average fitness for run x |
german_3_stdf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Standard deviation of fitness for run x |
german_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 |
german_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 |
german_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 |
german_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 |
german_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 |
german_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 |