param.txt

# THIS IS A PARAMETER FILE FOR THE STREAM-MOEA ALGORITHM
#This a comment. Comments starts with a '#' sign.
algorithm = stream-moea

# The input data, it must be a stream stored in an arff file. Others kinds of streams should be added in next versions.
inputData = taxis.arff

# The paths of the results files, separated by whitespaces, in this order: training QMs, test QMs for each rule, test QMs summary and rules.
outputData = taxis_tra_qua.txt    taxis_tst_qua.txt     taxis_quaSumm.txt     taxis_rules.txt

# The number of collected instances before starting the genetic algorithm.
period = 2500

# Parameters of the genetic algorithm
seed = 1
RulesRepresentation = dnf
nLabels = 7
nGen = 70
popLength = 50
crossProb = 0.8
mutProb = 0.1


# Use this to set the evaluator: "byObjectives" uses presence and objective values in previous timestamps. Other value use only presence in previous steps.
# Use: "byDiversity" to apply the evaluator based in the application of the decay factor on the diversity measure
Evaluator = byDiversity

# The size of the sliding window to be used by the evaluator.
SlidingWindowSize = 5

# The objectives to be used in the genetic algorithm.
# They must match with the name of the class that represent the quality measure
Obj1 = WRAccNorm
Obj2 = SuppDiff
Obj3 = NULL

# The diversity measure to be used. Useful for process like Token Competition.
diversity = WRAccNorm

# The different filter applied at the end of the evolutionary process. It will be applied in 
# order, i.e., the first one is applied over the result, then the second is applied over the result extra-dnf-7-2500cted from the first one and so on.
filter = TokenCompetition