The Evolutionary Pre-Processor (version 3.0) Batch Run Report |
![]() |
Batch Details
Batch run name | vehicle_2 |
Description | Vehicle 2 on Fourier |
This report file | final/vehicle_2/vehicle_2_report.html |
data file | /home/cssip/jsherrah/EPrep3/data/vehicle_2.dat |
Time of completion | Tue Jun 2 12:46:03 1998 |
Duration of Batch | 45 hours, 18 minutes, 35 seconds |
Random Seed | 578848808 (from clock) |
Average generations per run | 48.00 |
Average failed feature creations per run | 2793.80 |
Average fitness evalutions per run | 116911.80 |
Test Set Improvement | 0.94 % |
Data Partition
Class | Training | Validation | Test | Total |
0 | 106 | 53 | 53 | 212 |
1 | 109 | 54 | 54 | 217 |
2 | 109 | 55 | 54 | 218 |
3 | 99 | 49 | 51 | 199 |
Total | 423 | 211 | 212 | 846 |
Summary of Results
Original Classification Errors (%)
Classifier | Training | Validation | Test |
Parallelepiped(PPD) | 56.50 | 63.51 | 67.45 |
Maximum Likelihood(ML) | 7.09 | 17.54 | 18.40 |
Min. Distance to Means(MDTM) | 59.34 | 64.45 | 60.38 |
|
|
|
|
|
|
|
|
|
1 | 9.93 | 14.22 | 17.45 | 0.348 | 13 | 12 | 15 | ML |
2 | 9.22 | 14.22 | 16.98 | 0.583 | 14 | 15 | 22 | ML |
3 | 8.75 | 15.64 | 20.28 | 0.145 | 14 | 18 | 284 | ML |
4 | 8.04 | 16.59 | 17.92 | 0.500 | 16 | 16 | 33 | ML |
5 | 9.46 | 14.22 | 20.28 | 0.111 | 14 | 18 | 166 | ML |
6 | 9.46 | 15.17 | 23.58 | 0.008 | 15 | 15 | 30 | ML |
7 | 5.91 | 14.22 | 18.87 | 0.203 | 17 | 18 | 81 | ML |
8 | 8.04 | 15.17 | 15.57 | 0.901 | 14 | 14 | 18 | ML |
9 | 8.04 | 16.11 | 18.87 | 0.184 | 17 | 18 | 285 | ML |
10 | 8.75 | 15.64 | 17.45 | 0.500 | 13 | 13 | 14 | ML |
Ave. | 8.56 (1.09 ) | 15.12 (0.83 ) | 18.73 (2.13 ) | 0.35 (0.26 ) | 14.70 (1.42 ) | 15.70 (2.15 ) | 94.80 (104.57) | ML |
|
|
Total | ||||
|
|
|
|
|||
Ground Truth |
|
36 | 12 | 2 | 3 | 53 |
|
14 | 38 | 1 | 1 | 54 | |
|
0 | 0 | 53 | 1 | 54 | |
|
0 | 3 | 0 | 48 | 51 | |
|
50 | 53 | 56 | 53 | 212 |
Average Operator Probabilities
Operator | Average Probability |
Delete-Feature Mutation | 0.094 |
Add-Feature Mutation | 0.099 |
Hoist Mutation | 0.107 |
Truncate Mutation | 0.102 |
Swap Mutation | 0.106 |
One-Symbol Mutation | 0.100 |
All-Nodes Mutation | 0.094 |
One-Node Mutation | 0.092 |
Grow Mutation | 0.100 |
High-Level Crossover | 0.107 |
Number of Run Terminations attributed to each Criterion
Termination Criterion | Number of Terminations |
TP Criterion | 0 |
GL Criterion | 1 |
Max. Generations | 9 |
Client Abort | 0 |
Zero Validation Error | 0 |
Total | 10 |
Related Data Files
Description | Filename |
vehicle_2_gen.m | Matlab plot generation function |
vehicle_2_bogf_ave.{eps,gif} | Best-of-generation Fitness, averaged over 10 runs |
vehicle_2_bogv_ave.{eps,gif} | Best-of-generation Validation Set Error, averaged over 10 runs |
vehicle_2_avef_ave.{eps,gif} | Average fitness, averaged over 10 runs |
vehicle_2_stdf_ave.{eps,gif} | Standard deviation of fitness, averaged over 10 runs |
vehicle_2_nftr_ave.{eps,gif} | Average number of features per individual, averaged over 10 runs |
vehicle_2_nnode_ave.{eps,gif} | Average number of nodes per individual, averaged over 10 runs |
vehicle_2_nint_ave.{eps,gif} | Average number of introns per individual, averaged over 10 runs |
vehicle_2_ntrl_ave.{eps,gif} | Average number of RAT trials per individual, averaged over 10 runs |
vehicle_2_optimp_ave.{eps,gif} | Average improvement in fitness due to optimisation, averaged over 10 runs |
vehicle_2_opprob_ave.{eps,gif} | Average probability of each genetic operator, averaged over 10 runs |
vehicle_2_run_x.dat | Binary data file containing results of run x (read by Matlab functions) |
vehicle_2_bor_x.prep x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-run individual for run x |
vehicle_2_run_x.corr x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Feature correlation file for run x |
vehicle_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 |
vehicle_2_bogf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Best-of-generation Fitness for run x |
vehicle_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 |
vehicle_2_avef_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Average fitness for run x |
vehicle_2_stdf_x.{eps,gif} x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 |
Standard deviation of fitness for run x |
vehicle_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 |
vehicle_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 |
vehicle_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 |
vehicle_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 |
vehicle_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 |
vehicle_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 |