The Evolutionary Pre-Processor (version 3.0) Batch Run Report |
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Batch Details
Batch run name | titanic_3 |
Description | Titanic 3 on Gauss |
This report file | final/titanic_3/titanic_3_report.html |
data file | /home/cssip_a/jsherrah/data/titanic_3.dat |
Time of completion | Thu May 28 16:40:18 1998 |
Duration of Batch | 3 hours, 22 minutes, 47 seconds |
Random Seed | 2692754058 (from clock) |
Average generations per run | 25.20 |
Average failed feature creations per run | 9953.00 |
Average fitness evalutions per run | 159641.00 |
Test Set Improvement | 11.62 % |
Data Partition
Class | Training | Validation | Test | Total |
0 | 745 | 372 | 373 | 1490 |
1 | 355 | 178 | 178 | 711 |
Total | 1100 | 550 | 551 | 2201 |
Summary of Results
Original Classification Errors (%)
Classifier | Training | Validation | Test |
Parallelepiped(PPD) | 32.27 | 32.36 | 32.30 |
Min. Distance to Means(MDTM) | 31.36 | 31.27 | 32.30 |
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1 | 19.91 | 23.45 | 21.05 | 1.000 | 1 | 3 | 42 | MDTM |
2 | 21.27 | 22.55 | 21.60 | 1.000 | 2 | 3 | 104 | MDTM |
3 | 20.27 | 23.09 | 20.15 | 1.000 | 1 | 3 | 12 | MDTM |
4 | 20.55 | 23.09 | 20.51 | 1.000 | 1 | 3 | 35 | MDTM |
5 | 21.27 | 22.55 | 21.60 | 1.000 | 3 | 3 | 43 | MDTM |
6 | 20.27 | 23.09 | 20.15 | 1.000 | 1 | 3 | 18 | MDTM |
7 | 21.55 | 22.55 | 21.96 | 1.000 | 2 | 3 | 161 | MDTM |
8 | 21.27 | 22.55 | 21.60 | 1.000 | 1 | 3 | 40 | MDTM |
9 | 21.55 | 22.55 | 21.96 | 1.000 | 3 | 3 | 65 | MDTM |
10 | 21.64 | 22.18 | 20.69 | 1.000 | 2 | 3 | 48 | MDTM |
Ave. | 20.95 (0.60 ) | 22.76 (0.37 ) | 21.13 (0.68 ) | 1.00 (0.00 ) | 1.70 (0.78 ) | 3.00 (0.00 ) | 56.80 (42.32 ) | MDTM |
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Total | ||
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Ground Truth |
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354 | 19 | 373 |
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95 | 83 | 178 | |
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449 | 102 | 551 |
Average Operator Probabilities
Operator | Average Probability |
Delete-Feature Mutation | 0.108 |
Add-Feature Mutation | 0.111 |
Hoist Mutation | 0.107 |
Swap Mutation | 0.111 |
One-Symbol Mutation | 0.110 |
All-Nodes Mutation | 0.107 |
One-Node Mutation | 0.114 |
Grow Mutation | 0.111 |
High-Level Crossover | 0.120 |
Number of Run Terminations attributed to each Criterion
Termination Criterion | Number of Terminations |
TP Criterion | 7 |
GL Criterion | 1 |
Max. Generations | 2 |
Client Abort | 0 |
Zero Validation Error | 0 |
Total | 10 |
Related Data Files
Description | Filename |
titanic_3_gen.m | Matlab plot generation function |
titanic_3_bogf_ave.{eps,gif} | Best-of-generation Fitness, averaged over 10 runs |
titanic_3_bogv_ave.{eps,gif} | Best-of-generation Validation Set Error, averaged over 10 runs |
titanic_3_avef_ave.{eps,gif} | Average fitness, averaged over 10 runs |
titanic_3_stdf_ave.{eps,gif} | Standard deviation of fitness, averaged over 10 runs |
titanic_3_nftr_ave.{eps,gif} | Average number of features per individual, averaged over 10 runs |
titanic_3_nnode_ave.{eps,gif} | Average number of nodes per individual, averaged over 10 runs |
titanic_3_nint_ave.{eps,gif} | Average number of introns per individual, averaged over 10 runs |
titanic_3_ntrl_ave.{eps,gif} | Average number of RAT trials per individual, averaged over 10 runs |
titanic_3_optimp_ave.{eps,gif} | Average improvement in fitness due to optimisation, averaged over 10 runs |
titanic_3_opprob_ave.{eps,gif} | Average probability of each genetic operator, averaged over 10 runs |
titanic_3_run_x.dat | Binary data file containing results of run x (read by Matlab functions) |
titanic_3_bor_x.prep x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-run individual for run x |
titanic_3_run_x.corr x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Feature correlation file for run x |
titanic_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 |
titanic_3_bogf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-generation Fitness for run x |
titanic_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 |
titanic_3_avef_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average fitness for run x |
titanic_3_stdf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Standard deviation of fitness for run x |
titanic_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 |
titanic_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 |
titanic_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 |
titanic_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 |
titanic_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 |
titanic_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 |