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

 

Batch Details
Batch run name segment_2
Description Segment 2 on Hilbert
This report file final/segment_2/segment_2_report.html
data file /home/cssip/jsherrah/EPrep3/data/segment_2.dat
Time of completion Mon Jun 1 02:37:56 1998
Duration of Batch 11 hours, 11 minutes, 15 seconds
Random Seed 706879489 (from clock)
Average generations per run 28.30
Average failed feature creations per run 1116.20
Average fitness evalutions per run 74757.10
Test Set Improvement 10.38 %
 
 

Data Partition
 
Class Training Validation Test Total
0 165 82 83 330
1 165 84 81 330
2 165 82 83 330
3 165 82 83 330
4 165 82 83 330
5 165 83 82 330
6 165 82 83 330
Total 1155 577 578 2310

Summary of Results

  Original Classification Errors (%)
Classifier Training Validation Test
Maximum Likelihood(ML) 16.62 16.98 14.88

  EPrep Best-of-run Classification Errors (%)
Run
Training
Validation
Test
McNemar confidence
# Features
# Inputs
# Nodes
Classifier
1 5.80 4.85 5.19 1.000 6 6 23 ML
2 6.67 4.68 4.50 1.000 6 4 15 ML
3 7.36 6.93 8.13 1.000 8 7 14 ML
4 8.23 6.24 6.40 1.000 4 4 9 ML
5 9.70 7.63 9.34 0.999 6 10 63 ML
6 6.15 4.51 5.36 1.000 9 8 59 ML
7 7.71 5.37 5.54 1.000 5 5 16 ML
8 5.97 4.51 4.50 1.000 8 11 92 ML
9 7.01 5.72 6.75 1.000 7 6 17 ML
10 7.97 5.55 6.40 1.000 4 4 10 ML
Ave. 7.26 (1.14 ) 5.60 (1.01 ) 6.21 (1.48 ) 1.00 (0.00 ) 6.30 (1.62 ) 6.50 (2.38 ) 31.80 (27.35 ) ML

  Confusion matrix for Best Ever Individual from run 8
Class
Predicted
Total
1
2
3
4
5
6
7
Ground Truth
1
81 0 0 0 2 0 0 83
2
0 80 0 1 0 0 0 81
3
1 0 75 0 7 0 0 83
4
0 0 0 77 6 0 0 83
5
0 0 5 3 75 0 0 83
6
0 0 0 0 0 82 0 82
7
0 0 0 0 1 0 82 83
Total
82 80 80 81 91 82 82 578

Average Operator Probabilities
Operator Average Probability
Delete-Feature Mutation 0.096
Add-Feature Mutation 0.098
Hoist Mutation 0.096
Truncate Mutation 0.095
Swap Mutation 0.100
One-Symbol Mutation 0.104
All-Nodes Mutation 0.096
One-Node Mutation 0.096
Grow Mutation 0.104
High-Level Crossover 0.115
 

Number of Run Terminations attributed to each Criterion
Termination Criterion Number of Terminations
TP Criterion 0
GL Criterion 7
Max. Generations 3
Client Abort 0
Zero Validation Error 0
Total 10
 
 

Related Data Files
Description Filename
segment_2_gen.m Matlab plot generation function
segment_2_bogf_ave.{eps,gif} Best-of-generation Fitness, averaged over 10 runs
segment_2_bogv_ave.{eps,gif} Best-of-generation Validation Set Error, averaged over 10 runs
segment_2_avef_ave.{eps,gif} Average fitness, averaged over 10 runs
segment_2_stdf_ave.{eps,gif} Standard deviation of fitness, averaged over 10 runs
segment_2_nftr_ave.{eps,gif} Average number of features per individual, averaged over 10 runs
segment_2_nnode_ave.{eps,gif} Average number of nodes per individual, averaged over 10 runs
segment_2_nint_ave.{eps,gif} Average number of introns per individual, averaged over 10 runs
segment_2_ntrl_ave.{eps,gif} Average number of RAT trials per individual, averaged over 10 runs
segment_2_optimp_ave.{eps,gif} Average improvement in fitness due to optimisation, averaged over 10 runs
segment_2_opprob_ave.{eps,gif} Average probability of each genetic operator, averaged over 10 runs
segment_2_run_x.dat Binary data file containing results of run x (read by Matlab functions)
segment_2_bor_x.prep 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Best-of-run individual for run x
segment_2_run_x.corr 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Feature correlation file for run x
segment_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
segment_2_bogf_x.{eps,gif} 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Best-of-generation Fitness for run x
segment_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
segment_2_avef_x.{eps,gif} 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Average fitness for run x
segment_2_stdf_x.{eps,gif} 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Standard deviation of fitness for run x
segment_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
segment_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
segment_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
segment_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
segment_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
segment_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