config_tuning.ini

#ClassifierSize - max size of classifier
#SetAlpha - if False  alpha is assigned randomly to each classifier
#Alpha - fixed decision threshold, to use it set SetAlpha to True
[CLASSIFIER PARAMETERS]

ClassifierSize = 5
SetAlpha = False
Alpha = 0.5

#TrainingFraction - fraction of data to be training data 
#(100-TrainingFraction) - testing data
#CVFolds - number of folds for CV in parameter tuning
[DATA DIVISION]

TrainingFraction = 100
CVFolds = 2
Pairing = True
SetSeed = False

#MSegments, AlphaBin, LambdaBin - binarization parameters
[BINARIZATION PARAMETERS]

Binarize = True
MSegments = 50
AlphaBin = 0.5
LambdaBin = 0.1

#Ranges of parameters to tune
[PARAMETER TUNING]

Tuning = True
NumberOfSets = 2
TuneWeights = False
IterationLowerBound = 10 
IterationUpperBound = 30
IterationStep = 5
PopulationLowerBound = 50
PopulationUpperBound = 300
PopulationStep = 50
CrossoverLowerBound = 10
CrossoverUpperBound = 100
CrossoverStep = 10
MutationLowerBound = 10
MutationUpperBound = 100
MutationStep = 10
TournamentLowerBound = 10
TournamentUpperBound = 50
TournamentStep = 10
WeightLowerBound = 10
WeightUpperBound = 100
WeightStep = 10

# if tuning is set to False GA parameters may be set to constants
[GA PARAMETERS]

Iterations = 30
PopulationSize = 300
CrossoverProbability = 0.8
MutationProbability = 0.1
TournamentSize = 0.2

#SingleTestRepeats - number of repeats of a single GA run
[RUN PARAMETERS]

SingleTestRepeats = 5

#Elitism - if True the best found solutions are added to the population in each selection operation
[ALGORITHM PARAMETERS]

Elitism = True

#BaccWeight - weight for BACC in the classifier score
#Uniqueness - uniqueness option (related to calculation of CDD classifier score, default: True)
[OBJECTIVE FUNCTION]

Weight = 1.0
Uniqueness = True

#ProccessorNumb - number of available processors for parallel computation
[PARALELIZATION]

ProccessorNumb = 1