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

 

Batch Details
Batch run name vehicle_1
Description Vehicle 1 on Nyquist
This report file final/vehicle_1/vehicle_1_report.html
data file /home/cssip/jsherrah/EPrep3/data/vehicle_1.dat
Time of completion Mon Jun 1 01:39:37 1998
Duration of Batch 11 hours, 20 minutes, 3 seconds
Random Seed 18446744072244177578 (from clock)
Average generations per run 26.90
Average failed feature creations per run 2711.60
Average fitness evalutions per run 62820.30
Test Set Improvement -0.94 %
 
 

Data Partition
 
Class Training Validation Test Total
0 107 53 52 212
1 108 55 54 217
2 109 54 55 218
3 99 49 51 199
Total 423 211 212 846

Summary of Results

  Original Classification Errors (%)
Classifier Training Validation Test
Parallelepiped(PPD) 56.74 63.03 62.26
Maximum Likelihood(ML) 6.15 16.11 12.74
Min. Distance to Means(MDTM) 60.76 59.24 60.38

  EPrep Best-of-run Classification Errors (%)
Run
Training
Validation
Test
McNemar confidence
# Features
# Inputs
# Nodes
Classifier
1 7.09 15.17 12.74 0.264 16 17 96 ML
2 9.93 15.17 13.21 0.258 13 12 16 ML
3 6.62 13.27 15.09 0.055 15 17 66 ML
4 7.57 15.17 13.21 0.184 15 15 15 ML
5 9.22 13.27 13.68 0.174 13 13 13 ML
6 6.38 14.69 13.21 0.184 14 14 14 ML
7 6.15 13.74 14.15 0.084 17 18 146 ML
8 7.80 13.74 13.21 0.221 13 13 13 ML
9 9.22 13.27 13.68 0.174 13 13 15 ML
10 7.09 15.17 15.57 0.064 14 14 14 ML
Ave. 7.71 (1.25 ) 14.27 (0.83 ) 13.77 (0.86 ) 0.17 (0.07 ) 14.30 (1.35 ) 14.60 (1.96 ) 40.80 (44.36 ) ML

  Confusion matrix for Best Ever Individual from run 5
Class
Predicted
Total
1
2
3
4
Ground Truth
1
39 12 0 1 52
2
12 41 0 1 54
3
0 0 53 2 55
4
0 0 1 50 51
Total
51 53 54 54 212

Average Operator Probabilities
Operator Average Probability
Delete-Feature Mutation 0.095
Add-Feature Mutation 0.104
Hoist Mutation 0.107
Truncate Mutation 0.101
Swap Mutation 0.100
One-Symbol Mutation 0.093
All-Nodes Mutation 0.104
One-Node Mutation 0.107
Grow Mutation 0.096
High-Level Crossover 0.092
 

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
vehicle_1_gen.m Matlab plot generation function
vehicle_1_bogf_ave.{eps,gif} Best-of-generation Fitness, averaged over 10 runs
vehicle_1_bogv_ave.{eps,gif} Best-of-generation Validation Set Error, averaged over 10 runs
vehicle_1_avef_ave.{eps,gif} Average fitness, averaged over 10 runs
vehicle_1_stdf_ave.{eps,gif} Standard deviation of fitness, averaged over 10 runs
vehicle_1_nftr_ave.{eps,gif} Average number of features per individual, averaged over 10 runs
vehicle_1_nnode_ave.{eps,gif} Average number of nodes per individual, averaged over 10 runs
vehicle_1_nint_ave.{eps,gif} Average number of introns per individual, averaged over 10 runs
vehicle_1_ntrl_ave.{eps,gif} Average number of RAT trials per individual, averaged over 10 runs
vehicle_1_optimp_ave.{eps,gif} Average improvement in fitness due to optimisation, averaged over 10 runs
vehicle_1_opprob_ave.{eps,gif} Average probability of each genetic operator, averaged over 10 runs
vehicle_1_run_x.dat Binary data file containing results of run x (read by Matlab functions)
vehicle_1_bor_x.prep 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Best-of-run individual for run x
vehicle_1_run_x.corr 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Feature correlation file for run x
vehicle_1_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_1_bogf_x.{eps,gif} 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Best-of-generation Fitness for run x
vehicle_1_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_1_avef_x.{eps,gif} 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Average fitness for run x
vehicle_1_stdf_x.{eps,gif} 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Standard deviation of fitness for run x
vehicle_1_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_1_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_1_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_1_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_1_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_1_opprob_x.{eps,gif} 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Average probability of each genetic operator for run x