###############################################################
#Configuration file for the experiments
################################################################

#Multi-label data?
multi-label = 1

#Number of initial generated rules
number initial rules = 500

#Number of runs
number of runs = 10

#Number of levels
number of levels = 1

#Elitism
elitism number = 1

#Mutation
mutation rate = 0.4

#Probability of using a clausule in initialization
probability using clausule = 0.55

#Crossover
crossover rate = 0.9

#Paths datasets
path datasets = Datasets/

#Relational tests (0 - no relational tests / 1 - mix of propositional and relational tests)
relational tests = 0

#Datasets
dataset train = flags.train.arff
dataset valid = none
dataset test = flags.test.arff

#Target positions
target positions = [20-26]

#hierarchy type = DAG, Tree or Flat
hierarchy type = Flat

#Number of generation
number of generations = 300

#Size of tournament
size tournament = 2

#Maximun number of uncovered examples
max uncovered examples = 10

#Minimum covered examples per rule
min covered examples per rule = 5

#Maximum covered examples per rule
max covered examples per rule = 100

#Fitness function to use (VG, AUPRC, AUPRCxCoveredInstances, VGxCoveredInstances, VGxAUPRC)
fitness function = AUPRCxCoveredInstances

# Perform local search (1-Yes / 0-No)
local search = 0

# Crossocer type (1 - uniform with distance / 2 - normal uniform crossover)
crossover type = 1

#Threshold values to build PR curves
threshold values = [0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,68,70,72,74,76,78,80,82,84,86,88,90,92,94,96,98,100]