The Evolutionary Pre-Processor (version 3.0) Batch Run Report |
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Batch Details
Batch run name | german_2 |
Description | German 2 on Atlas |
This report file | final/german_2/german_2_report.html |
data file | /home/cssip/jsherrah/EPrep3/data/german_2.dat |
Time of completion | Tue Jun 2 11:57:00 1998 |
Duration of Batch | 13 hours, 49 minutes, 6 seconds |
Random Seed | 2861081218 (from clock) |
Average generations per run | 21.30 |
Average failed feature creations per run | 23592.80 |
Average fitness evalutions per run | 174387.30 |
Test Set Improvement | 1.60 % |
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) | 16.80 | 30.00 | 28.80 |
Min. Distance to Means(MDTM) | 40.40 | 33.20 | 41.20 |
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1 | 26.20 | 29.60 | 34.00 | 0.067 | 6 | 16 | 219 | ML |
2 | 23.40 | 22.80 | 28.00 | 0.618 | 14 | 15 | 32 | ML |
3 | 24.80 | 22.80 | 28.80 | 0.500 | 9 | 13 | 400 | ML |
4 | 19.80 | 24.00 | 27.20 | 0.729 | 16 | 17 | 149 | ML |
5 | 22.60 | 21.20 | 27.20 | 0.691 | 16 | 14 | 173 | ML |
6 | 22.80 | 23.60 | 30.00 | 0.359 | 16 | 19 | 356 | ML |
7 | 21.80 | 21.60 | 28.40 | 0.560 | 13 | 13 | 13 | ML |
8 | 22.20 | 24.80 | 30.40 | 0.248 | 14 | 14 | 14 | ML |
9 | 21.20 | 23.20 | 28.80 | 0.500 | 15 | 16 | 36 | ML |
10 | 20.60 | 25.20 | 26.80 | 0.770 | 17 | 17 | 94 | ML |
Ave. | 22.54 (1.82 ) | 23.88 (2.25 ) | 28.96 (2.02 ) | 0.50 (0.21 ) | 13.60 (3.32 ) | 15.40 (1.85 ) | 148.60(133.24) | ML |
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Total | ||
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Ground Truth |
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150 | 25 | 175 |
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43 | 32 | 75 | |
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193 | 57 | 250 |
Average Operator Probabilities
Operator | Average Probability |
Delete-Feature Mutation | 0.095 |
Add-Feature Mutation | 0.103 |
Hoist Mutation | 0.098 |
Truncate Mutation | 0.104 |
Swap Mutation | 0.101 |
One-Symbol Mutation | 0.097 |
All-Nodes Mutation | 0.100 |
One-Node Mutation | 0.101 |
Grow Mutation | 0.099 |
High-Level Crossover | 0.103 |
Number of Run Terminations attributed to each Criterion
Termination Criterion | Number of Terminations |
TP Criterion | 0 |
GL Criterion | 10 |
Max. Generations | 0 |
Client Abort | 0 |
Zero Validation Error | 0 |
Total | 10 |
Related Data Files
Description | Filename |
german_2_gen.m | Matlab plot generation function |
german_2_bogf_ave.{eps,gif} | Best-of-generation Fitness, averaged over 10 runs |
german_2_bogv_ave.{eps,gif} | Best-of-generation Validation Set Error, averaged over 10 runs |
german_2_avef_ave.{eps,gif} | Average fitness, averaged over 10 runs |
german_2_stdf_ave.{eps,gif} | Standard deviation of fitness, averaged over 10 runs |
german_2_nftr_ave.{eps,gif} | Average number of features per individual, averaged over 10 runs |
german_2_nnode_ave.{eps,gif} | Average number of nodes per individual, averaged over 10 runs |
german_2_nint_ave.{eps,gif} | Average number of introns per individual, averaged over 10 runs |
german_2_ntrl_ave.{eps,gif} | Average number of RAT trials per individual, averaged over 10 runs |
german_2_optimp_ave.{eps,gif} | Average improvement in fitness due to optimisation, averaged over 10 runs |
german_2_opprob_ave.{eps,gif} | Average probability of each genetic operator, averaged over 10 runs |
german_2_run_x.dat | Binary data file containing results of run x (read by Matlab functions) |
german_2_bor_x.prep x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-run individual for run x |
german_2_run_x.corr x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Feature correlation file for run x |
german_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 |
german_2_bogf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-generation Fitness for run x |
german_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 |
german_2_avef_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average fitness for run x |
german_2_stdf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Standard deviation of fitness for run x |
german_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 |
german_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 |
german_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 |
german_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 |
german_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 |
german_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 |