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import Orange
data = Orange.data.Table("iris")
learner = Orange.classification.CN2UnorderedLearner()
# consider up to 10 solution streams at one time
learner.rule_finder.search_algorithm.beam_width = 10
# continuous value space is constrained to reduce computation time
learner.rule_finder.search_strategy.constrain_continuous = True
# found rules must cover at least 15 examples
learner.rule_finder.general_validator.min_covered_examples = 15
# found rules may combine at most 2 selectors (conditions)
learner.rule_finder.general_validator.max_rule_length = 2
classifier = learner(data)
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