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

 

Batch Details
Batch run name segment_1
Description Segment 1 on Gauss
This report file final/segment_1/segment_1_report.html
data file /home/cssip/jsherrah/EPrep3/data/segment_1.dat
Time of completion Mon Jun 1 16:17:30 1998
Duration of Batch 45 hours, 59 minutes, 14 seconds
Random Seed 2281703552 (from clock)
Average generations per run 32.80
Average failed feature creations per run 1161.90
Average fitness evalutions per run 118756.20
Test Set Improvement 80.80 %
 
 

Data Partition
 
Class Training Validation Test Total
0 165 82 83 330
1 165 82 83 330
2 165 82 83 330
3 165 83 82 330
4 165 83 82 330
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) 85.71 85.79 85.64

  EPrep Best-of-run Classification Errors (%)
Run
Training
Validation
Test
McNemar confidence
# Features
# Inputs
# Nodes
Classifier
1 5.97 6.76 7.61 1.000 7 10 88 ML
2 7.45 7.28 6.23 1.000 8 10 107 ML
3 5.80 6.93 6.06 1.000 9 11 100 ML
4 6.67 7.28 5.88 1.000 4 11 182 ML
5 5.89 5.37 4.84 1.000 9 6 28 ML
6 9.09 9.53 9.00 1.000 6 11 148 ML
7 7.01 6.76 7.61 1.000 10 11 162 ML
8 6.58 6.93 5.71 1.000 4 4 10 ML
9 7.97 8.67 7.96 1.000 7 11 118 ML
10 6.93 6.93 7.44 1.000 9 11 305 ML
Ave. 6.94 (0.97 ) 7.24 (1.07 ) 6.83 (1.21 ) 1.00 (0.00 ) 7.30 (2.00 ) 9.60 (2.37 ) 124.80(79.09 ) ML

  Confusion matrix for Best Ever Individual from run 5
Class
Predicted
Total
1
2
3
4
5
6
7
Ground Truth
1
81 0 1 0 1 0 0 83
2
0 81 0 2 0 0 0 83
3
1 0 74 0 8 0 0 83
4
0 0 1 78 3 0 0 82
5
0 0 8 1 73 0 0 82
6
0 0 0 2 0 80 0 82
7
0 0 0 0 0 0 83 83
Total
82 81 84 83 85 80 83 578

Average Operator Probabilities
Operator Average Probability
Delete-Feature Mutation 0.092
Add-Feature Mutation 0.092
Hoist Mutation 0.102
Truncate Mutation 0.097
Swap Mutation 0.101
One-Symbol Mutation 0.101
All-Nodes Mutation 0.100
One-Node Mutation 0.095
Grow Mutation 0.099
High-Level Crossover 0.119
 

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
segment_1_gen.m Matlab plot generation function
segment_1_bogf_ave.{eps,gif} Best-of-generation Fitness, averaged over 10 runs
segment_1_bogv_ave.{eps,gif} Best-of-generation Validation Set Error, averaged over 10 runs
segment_1_avef_ave.{eps,gif} Average fitness, averaged over 10 runs
segment_1_stdf_ave.{eps,gif} Standard deviation of fitness, averaged over 10 runs
segment_1_nftr_ave.{eps,gif} Average number of features per individual, averaged over 10 runs
segment_1_nnode_ave.{eps,gif} Average number of nodes per individual, averaged over 10 runs
segment_1_nint_ave.{eps,gif} Average number of introns per individual, averaged over 10 runs
segment_1_ntrl_ave.{eps,gif} Average number of RAT trials per individual, averaged over 10 runs
segment_1_optimp_ave.{eps,gif} Average improvement in fitness due to optimisation, averaged over 10 runs
segment_1_opprob_ave.{eps,gif} Average probability of each genetic operator, averaged over 10 runs
segment_1_run_x.dat Binary data file containing results of run x (read by Matlab functions)
segment_1_bor_x.prep 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Best-of-run individual for run x
segment_1_run_x.corr 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Feature correlation file for run x
segment_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
segment_1_bogf_x.{eps,gif} 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Best-of-generation Fitness for run x
segment_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
segment_1_avef_x.{eps,gif} 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Average fitness for run x
segment_1_stdf_x.{eps,gif} 
x = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
Standard deviation of fitness for run x
segment_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
segment_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
segment_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
segment_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
segment_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
segment_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