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

  EPrep Best-of-run Classification Errors (%)
Run
Training
Validation
Test
McNemar confidence
# Features
# Inputs
# Nodes
Classifier
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

  Confusion matrix for Best Ever Individual from run 1
Class
Predicted
Total
1
2
3
4
Ground Truth
1
36 12 2 3 53
2
14 38 1 1 54
3
0 0 53 1 54
4
0 3 0 48 51
Total
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