The Evolutionary Pre-Processor (version 3.0)
Batch Run Report

 

Batch Details
Batch run name vehicle_3
Description Vehicle 3 on Nyquist
This report file final/vehicle_3/vehicle_3_report.html
data file /home/cssip/jsherrah/EPrep3/data/vehicle_3.dat
Time of completion Mon Jun 1 22:05:27 1998
Duration of Batch 12 hours, 53 minutes, 52 seconds
Random Seed 18446744072233820835 (from clock)
Average generations per run 39.80
Average failed feature creations per run 2725.60
Average fitness evalutions per run 70973.90
Test Set Improvement -2.36 %
 
 

Data Partition
 
Class Training Validation Test Total
0 107 53 52 212
1 108 54 55 217
2 109 54 55 218
3 99 50 50 199
Total 423 211 212 846

Summary of Results

  Original Classification Errors (%)
Classifier Training Validation Test
Parallelepiped(PPD) 59.81 63.98 65.57
Maximum Likelihood(ML) 5.91 18.48 14.15
Min. Distance to Means(MDTM) 60.76 57.82 63.21

  EPrep Best-of-run Classification Errors (%)
Run
Training
Validation
Test
McNemar confidence
# Features
# Inputs
# Nodes
Classifier
1 10.64 14.69 17.45 0.036 14 13 17 ML
2 12.29 13.74 16.51 0.090 12 12 12 ML
3 10.64 14.69 15.09 0.274 13 13 15 ML
4 10.40 15.17 15.57 0.218 13 13 14 ML
5 11.82 13.74 14.15 0.248 13 13 13 ML
6 8.75 16.11 13.21 0.736 15 15 15 ML
7 12.29 13.74 16.51 0.090 12 12 12 ML
8 11.35 15.17 18.87 0.039 15 15 34 ML
9 9.22 16.11 15.57 0.169 15 18 340 ML
10 6.38 15.64 14.15 0.394 18 17 20 ML
Ave. 10.38 (1.75 ) 14.88 (0.88 ) 15.71 (1.61 ) 0.23 (0.20 ) 14.00 (1.73 ) 14.10 (1.97 ) 49.20 (97.13 ) ML

  Confusion matrix for Best Ever Individual from run 2
Class
Predicted
Total
1
2
3
4
Ground Truth
1
39 13 0 0 52
2
14 38 0 3 55
3
0 0 51 4 55
4
1 0 0 49 50
Total
54 51 51 56 212

Average Operator Probabilities
Operator Average Probability
Delete-Feature Mutation 0.096
Add-Feature Mutation 0.104
Hoist Mutation 0.092
Truncate Mutation 0.102
Swap Mutation 0.102
One-Symbol Mutation 0.092
All-Nodes Mutation 0.095
One-Node Mutation 0.099
Grow Mutation 0.098
High-Level Crossover 0.120
 

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
vehicle_3_gen.m Matlab plot generation function
vehicle_3_bogf_ave.{eps,gif} Best-of-generation Fitness, averaged over 10 runs
vehicle_3_bogv_ave.{eps,gif} Best-of-generation Validation Set Error, averaged over 10 runs
vehicle_3_avef_ave.{eps,gif} Average fitness, averaged over 10 runs
vehicle_3_stdf_ave.{eps,gif} Standard deviation of fitness, averaged over 10 runs
vehicle_3_nftr_ave.{eps,gif} Average number of features per individual, averaged over 10 runs
vehicle_3_nnode_ave.{eps,gif} Average number of nodes per individual, averaged over 10 runs
vehicle_3_nint_ave.{eps,gif} Average number of introns per individual, averaged over 10 runs
vehicle_3_ntrl_ave.{eps,gif} Average number of RAT trials per individual, averaged over 10 runs
vehicle_3_optimp_ave.{eps,gif} Average improvement in fitness due to optimisation, averaged over 10 runs
vehicle_3_opprob_ave.{eps,gif} Average probability of each genetic operator, averaged over 10 runs
vehicle_3_run_x.dat Binary data file containing results of run x (read by Matlab functions)
vehicle_3_bor_x.prep 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Best-of-run individual for run x
vehicle_3_run_x.corr 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Feature correlation file for run x
vehicle_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
vehicle_3_bogf_x.{eps,gif} 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Best-of-generation Fitness for run x
vehicle_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
vehicle_3_avef_x.{eps,gif} 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Average fitness for run x
vehicle_3_stdf_x.{eps,gif} 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Standard deviation of fitness for run x
vehicle_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
vehicle_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
vehicle_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
vehicle_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
vehicle_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
vehicle_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