att3 = Attribute("location")
att3.add("home", "work", "other")
#add the attributes
mySet.addDefinition(att) # wifi
mySet.addDefinition(att3) # location
#select classifier
learner = RulesLearner('full_likelihood', mySet)
learner.setTemplateRuleLearnerName("[WiFi] <= When [Location] ")
#not necessary as learner already has the set
#rule.learner = FullLikelihood(mySet)
print("Action " + learner.getAction())
parameters = [att.getName(), att3.getName()]
learner.setFieldNames(parameters)
learner.setTreshold(0.7)
learner.setMinSamples(2)
#add "on" <- "home", 4 times
sn1 = ["on", "home"]
map(learner.addSample, [sn1] * 4)
#add "off" <- "home", 1 times
s4 = ["off", "home"]
learner.addSample(s4)
