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Last update: February 19, 2014


Settings

General Settings

This is the list of settings that can be changed using the job files (settings node) in GeneXproServer 5.0. The values in the key columns are the identifiers that must be used in the "key" attribute of the setting node.

Note that not all settings' values are checked by GeneXproServer. It is advisable to test the values in GeneXproTools before using them in GeneXproServer.

KeyData TypeDefinition

Population Size and Model Structure
Chromosomes int positive [1 4096] Number of Chromosomes
HeadSize int positive [1 256] Head Size
Genes int positive [1 64] Number of Genes
LinkingFunction List Linking Function

Sampling
TrainingRecords int positive Size of the Training Set
TrainingSamplingType int positive [0 10] Sampling Type for the Training Set
ValidationRecords int positive Size of the Validation Set
TestingSamplingType int positive [0 10] Sampling Type for the Validation Set
MiniBatchMode [0 1] Turn on Mini Batch
MiniBatchModePeriod int Mini Batch Period value

Rounding Threshold
RoundingThresholdType List Rounding Threshold Type
RoundingThreshold float Rounding Threshold Value
LogisticRoundingThresholdBins int Number of Bins (Logistic Rounding Threshold)

Simple Model (Fitness Function)
SimpleModel List Fitness Function Reference Simple Model
PredictorVariable variable index Predictor Variable Index

Structure Pressure (Fitness Function)
SetParsimonyPressure [0 1] Turn on Parsimony Pressure
ParsimonyPressureRate positive float [0 1] Parsimony Pressure Rate
SetVariablePressure [0 1] Turn on Variable Pressure
VariablePressureRate positive float [0 1] Variable Pressure Rate

Fitness Function
FitnessFunction List Fitness Function
CostGainFN float negative False Negative Cost
CostGainFP float negative False Positive Cost
CostGainTN float True Negative Cost
CostGainTP float True Positive Cost
Increment float Increment Value
InnerMargin float Inner Margin Value
OuterMargin float Outer Margin Value
Reward float positive Reward Value
Punishment float Punishment Value
SelectionRange float Selection Range Value
Precision float Precision Value
Beta float positive Beta Value (F Measure Fitness)
LowerBound float Lower Bound
UpperBound float Upper Bound
Bins int Number of Bins (Fitness Functions)

Custom Fitness
CustomFitnessFunction string Custom Fitness Function Code
CustomFitnessTimeout seconds Custom Fitness Timeout Value

Complexity Increase
SetComplexityIncrease [0 1] Turn on Complexity Increase
ComplexityIncreaseNumberOfTries int positive [1 32767] Number of Tries
ComplexityIncreaseGenerationsWithoutChange int positive [1 32767] Number of Generations without Change
ComplexityIncreaseMaxComplexity genes [1 64] Maximum Complexity Value

Time Series Transformation
TimeSeriesDelayTime int positive  Delay Time Value
TimeSeriesEmbeddingDimension int positive  Embedding Dimension Value
TimeSeriesTestingPredictions int positive  Number of Testing Predictions
Change Prediction Mode -- --

Random Numerical Constants
UseRNC [0 1] Turn on Random Constants
ConstantsPerGene int positive [1 100] Number of Random Constants per Gene
DataTypeRNC List Random Constants Data Type (float/integer)
UpperBoundRNC float Random Constants Upper Bound
LowerBoundRNC float Random Constants Lower Bound

Genetic Operators
BestCloningRate positive float [0 1] Best Cloning Rate
BiasedLeafMutationRate positive float [0 1] Biased Leaf Mutation Rate
BiasedMutationRate positive float [0 1] Biased Mutation Rate
ConservativeFunctionMutationRate positive float [0 1] Conservative Function Mutation Rate
ConservativeMutationRate positive float [0 1] Conservative Mutation Rate
ConservativePermutationRate positive float [0 1] Conservative Permutation Rate
FunctionInsertionRate positive float [0 1] Function Insertion Rate
GeneRecRate positive float [0 1] Gene Recombination Rate
GeneTranspRate positive float [0 1] Gene Transposition Rate
ISRate positive float [0 1] IS Transposition Rate
InversionRate positive float [0 1] Inversion Rate
LeafMutationRate positive float [0 1] Leaf Mutation Rate
MutationRate positive float [0 1] Mutation Rate
OnePointRecRate positive float [0 1] One Point Recombination Rate
PermutationRate positive float [0 1] Permutation Rate
RISRate positive float [0 1] RIS Transposition Rate
RandomChromosomesRate positive float [0 1] Random Chromosomes Rate
RandomCloningRate positive float [0 1] Random Cloning Rate
StumblingMutationRate positive float [0 1] Stumbling Mutation Rate
TailInversionRate positive float [0 1] Tail Inversion Rate
TailMutationRate positive float [0 1] Tail Mutation Rate
TwoPointRecRate positive float [0 1] Two Point Recombination Rate
UniformGeneRecombinationRate positive float [0 1] Uniform Gene Recombination Rate
UniformRecombinationRate positive float [0 1] Uniform Recombination Rate

Genetic Operators - Random Constants
ConstantFineTuningRateRNC positive float [0 1] Constant Fine Tuning Rate
ConstantInsertionRateRNC positive float [0 1] Constant Insertion Rate
ConstantRangeFindingRateRNC positive float [0 1] Constant Range Finding Rate
PermutationDcRateRNC positive float [0 1] Dc Permutation Rate
DcInversionRateRNC positive float [0 1] Dc Inversion Rate
DcMutationRateRNC positive float [0 1] Dc Mutation Rate
DcTranspRateRNC positive float [0 1] Dc Transposition Rate
MutationRateRNC positive float [0 1] RNC Mutation Rate

Other Settings
Author string Author's Name
Comments string Run Comments
UseUDFs [0 1] Turn on UDFs
FavoriteStatistic List Set Favorite Statistic
Math & Boolean Functions -- --

 

 

Linking Functions

The table below lists the values that can be used for the setting LinkingFunction. For example, the code below sets the Linking Function to Subtraction:

<setting key='LinkingFunction' value='1'/>
Linking FunctionValue

Mathematical Linking Functions
Addition 0
Subtraction 1
Multiplication 2
Division 3
Avg2 98
Min92
Max95

Boolean Linking Functions
AND 10001
OR 10002
NAND 10003
NOR 10004
OR 10005
NXOR 10006
Less Than 10022
Greater Than10023
Less Or Equal 10024
Greater Or Equal 10025

 

 

Simple Models (Fitness Functions)

The table below lists the values that can be used for the setting SimpleModel. For example, the code below sets the SimpleModel to Average Simple Model:

<setting key='SimpleModel' value='1'/>


And the code below shows how to set the PredictorVariable to d1 for the SimpleModel Predictor Variable:

<setting key='SimpleModel' value='3'/>
<setting key='PredictorVariable' value='1'/>

Simple ModelValue

Classification, Logistic Regression, Regression & Time Series Prediction
Target Average0
Target Midrange 4
Target Median 5
Average Simple Model 1
Random Target Output 2
Predictor Variable 3

Logic Synthesis
Target Majority 6
Majority Simple Model7
Random Target Output 2
Predictor Variable 3

 

 

Rounding Threshold Types

The table below lists the values that can be used for the setting RoundingThresholdType. For example, the code below sets the Rounding Threshold Type to Average:

<setting key='RoundingThresholdType' value='2'/>
Rounding Threshold TypeValue
User Defined0
ROC1
Average2
Midrange3
Midhinge4
Class Proportions5
Active Model6
RMS7
Interdecile Mean8
Interquartile Mean9
Trimean10
Logistic11
Large Margin13

 

 

Fitness Functions

The table below lists the values that can be used for the setting FitnessFunction. For example, the code below sets the Fitness Function to Absolute Hits with RRSE:

<setting key='FitnessFunction' value='120'/>
Fitness FunctionValue

Regression & Time Series Prediction
Relative Hits with RMSE116
Relative Hits with RRSE117
Relative Hits with RRSE 2118
Absolute Hits with RMSE119
Absolute Hits with RRSE120
Absolute Hits with RRSE 2121
Relative Error with SR0
Relative Error/Hits1
Absolute Error with SR2
Absolute Error/Hits3
Trends with Punishment79
Bounded Trends86
Trends R2 with Punishment103
Bounded Trends R2104
MSE5
RMSE6
MAE7
RSE8
RRSE9
RAE10
RSE 295
RRSE 296
RAE 297
Weighted MSE80
Weighted RMSE81
Weighted MAE82
Weighted RSE83
Weighted RRSE84
Weighted RAE85
Weighted RSE 298
Weighted RRSE 299
Weighted RAE 2100
Enhanced MSE28
Enhanced MAE30
Enhanced RSE31
Enhanced RAE33
Enhanced RSE 2101
Enhanced RAE 2102
Quantile MSE87
Quantile RMSE88
Quantile MAE89
Quantile RSE90
Quantile RRSE91
Quantile RAE92
R-square4
Bounded R-square29
Positive Correl26
Bounded Positive Correl32
Unsupervised Free-form Features128
Custom13

Classification
ROC Measure71
Bounded ROC72
ROC with MSE73
Rank Measure74
Bounded Rank75
Rank with MSE76
Maximum Likelihood112
Hinge Loss124
Logistic RMSE113
Dual Margin24
Margin with Penalty25
Triple Margin49
Bounded Triple Margin50
Enhanced Triple Margin51
Bounded Enhanced Triple Margin52
Entropy17
Entropy with MSE65
Purity20
Purity with MSE66
Positive Correl15
Positive Correl with MSE77
Bounded Positive Correl27
Class Variation126
MSE53
RMSE54
MAE55
RSE56
RRSE57
RAE58
RSE 2105
RRSE 2106
RAE 2107
Enhanced MSE16
Enhanced MAE18
Enhanced RSE19
Enhanced RAE21
Enhanced RSE 2108
Enhanced RAE 2109
Hits with Punishment11
Cost/Gain Matrix23
Sensitivity/Specificity12
PPV/NPV14
SSPN22
F Measure122
Jaccard Similarity93
Matthews Correl67
Matthews Correl with MSE68
False Balance129
Enhanced False Balance130
Relative False Balance131
Enhanced Relative False Balance132
Unsupervised Free-form Features127
Custom13

Logistic Regression
ROC Measure71
Bounded ROC72
ROC with MSE73
Symmetric ROC69
Bounded Symmetric ROC70
Rank Measure74
Bounded Rank75
Rank with MSE76
Quantile Spread61
Bounded Quantile Spread62
Quantile Spread with MSE63
Maximum Likelihood114
Hinge Loss125
Logistic RMSE115
Dual Margin24
Margin with Penalty25
Triple Margin49
Bounded Triple Margin50
Enhanced Triple Margin51
Bounded Enhanced Triple Margin52
Entropy17
Entropy with MSE65
Purity20
Purity with MSE66
R-square59
Bounded R-square60
Positive Correl15
Positive Correl with MSE77
Bounded Positive Correl27
Class Variation126
MSE53
RMSE54
MAE55
RSE56
RRSE57
RAE58
RSE 2105
RRSE 2106
RAE 2107
Enhanced MSE16
Enhanced MAE18
Enhanced RSE19
Enhanced RAE21
Enhanced RSE 2108
Enhanced RAE 2109
Hits with Punishment11
Cost/Gain Matrix23
Sensitivity/Specificity12
PPV/NPV14
SSPN22
F Measure122
Jaccard Similarity93
Matthews Correl67
Matthews Correl with MSE68
False Balance129
Enhanced False Balance130
Relative False Balance131
Enhanced Relative False Balance132
Unsupervised Free-form Features127
Custom13

Logic Synthesis
Hits with Punishment34
Cost/Gain Matrix35
Sensitivity/Specificity40
PPV/NPV41
SSPN42
F Measure123
Jaccard Similarity94
Matthews Correl44
Matthews Correl with MSE64
Entropy36
Entropy with MSE38
Purity37
Purity with MSE39
Positive Correl43
Positive Correl with MSE78
Enhanced MSE45
Enhanced MAE46
Enhanced RSE47
Enhanced RAE48
Enhanced RSE 2110
Enhanced RAE 2111
Custom13

 

 

Random Numerical Constants Type

The table below lists the values that can be used for the setting DataTypeRNC. For example, the code below sets the Random Numerical Constants Type to Floating-Point values:

<setting key='DataTypeRNC' value='1'/>

Data TypeValue
Integer0
Floating-Point1

 

 

Favorite Statistics

The table below lists the values that can be used for the setting FavoriteStatistic. For example, the code below sets the Favorite Statistic to RMSE:

<setting key='FavoriteStatistic' value='17'/>

StatisticValue

Regression & Time Series Prediction
MSE16
RMSE17
MAE18
RSE20
RRSE21
RAE19
Correlation Coefficient22
R-square2
Outliers15
Hits37
Up/Down Accuracy40
Up/Down Error41
Up/Down Hits42
Up/Down Errors43

Classification & Logistic Regression
Accuracy5
Error6
Hits38
Errors39
Sensitivity7
Specificity8
Positive Predictive Value9
Negative Predictive Value10
Recall33
Precision34
F1 Measure35
Jaccard Similarity31
Matthews Correlation Coefficient32
Pearson Correlation Coefficient22
R-square2
Area Under the ROC Curve36
MSE16
RMSE17
MAE18
RSE20
RRSE21
RAE19

Logic Synthesis
Accuracy5
Error6
Hits38
Errors39
Sensitivity7
Specificity8
Positive Predictive Value9
Negative Predictive Value10
Recall33
Precision34
F1 Measure35
Jaccard Similarity31
Matthews Correlation Coefficient32
Pearson Correlation Coefficient22
R-square2
MSE16
RMSE17
MAE18
RSE20
RRSE21
RAE19

 

 


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