def test_instantiations(self):
"""
Tests instantiating classes.
"""
cname = "weka.attributeSelection.BestFirst"
options = ["-D", "1", "-N", "5"]
search = attribute_selection.ASSearch(classname=cname, options=options)
self.assertIsNotNone(search,
msg="Search should not be None: " + cname + "/" +
str(options))
self.assertEqual(cname, search.classname, msg="Classnames differ!")
cname = "weka.attributeSelection.CfsSubsetEval"
options = ["-P", "1", "-E", "1"]
evaluation = attribute_selection.ASEvaluation(classname=cname,
options=options)
self.assertIsNotNone(evaluation,
msg="Evaluation should not be None: " + cname +
"/" + str(options))
self.assertEqual(cname, evaluation.classname, msg="Classnames differ!")
attsel = attribute_selection.AttributeSelection()
self.assertIsNotNone(search,
msg="AttributeSelection should not be None!")
attsel.search(search)
attsel.evaluator(evaluation)
def test_ranking(self):
"""
Tests ranking of attributes.
"""
loader = converters.Loader(classname="weka.core.converters.ArffLoader")
data = loader.load_file(self.datafile("anneal.arff"))
self.assertIsNotNone(data)
data.class_is_last()
search = attribute_selection.ASSearch(
classname="weka.attributeSelection.Ranker", options=["-N", "-1"])
self.assertIsNotNone(search, msg="Search should not be None!")
evaluation = attribute_selection.ASEvaluation(
"weka.attributeSelection.InfoGainAttributeEval")
self.assertIsNotNone(evaluation, msg="Evaluation should not be None!")
attsel = attribute_selection.AttributeSelection()
self.assertIsNotNone(attsel,
msg="AttributeSelection should not be None!")
attsel.ranking(True)
attsel.folds(2)
attsel.crossvalidation(True)
attsel.seed(42)
attsel.search(search)
attsel.evaluator(evaluation)
attsel.select_attributes(data)
self.assertGreater(len(str(attsel.ranked_attributes)),
0,
msg="results_string should get produced")
self.assertGreater(len(attsel.results_string),
0,
msg="results_string should get produced")
def test_reduce(self):
"""
Tests reducing of attributes.
"""
loader = converters.Loader(classname="weka.core.converters.ArffLoader")
data = loader.load_file(self.datafile("anneal.arff"))
self.assertIsNotNone(data)
data.class_is_last()
cname = "weka.attributeSelection.BestFirst"
options = ["-D", "1", "-N", "5"]
search = attribute_selection.ASSearch(classname=cname, options=options)
self.assertIsNotNone(search, msg="Search should not be None: " + cname + "/" + str(options))
cname = "weka.attributeSelection.CfsSubsetEval"
options = ["-P", "1", "-E", "1"]
evaluation = attribute_selection.ASEvaluation(classname=cname, options=options)
self.assertIsNotNone(evaluation, msg="Evaluation should not be None: " + cname + "/" + str(options))
attsel = attribute_selection.AttributeSelection()
self.assertIsNotNone(search, msg="AttributeSelection should not be None!")
attsel.search(search)
attsel.evaluator(evaluation)
attsel.select_attributes(data)
reduced = attsel.reduce_dimensionality(data)
self.assertEqual(attsel.number_attributes_selected + 1, reduced.num_attributes, msg="number of attributes differs")
self.assertEqual(data.num_instances, reduced.num_instances, msg="number of rows differs")
def test_attribute_selection(self):
"""
Tests attribute selection.
"""
loader = converters.Loader(classname="weka.core.converters.ArffLoader")
data = loader.load_file(self.datafile("anneal.arff"))
self.assertIsNotNone(data)
data.class_is_last()
cname = "weka.attributeSelection.BestFirst"
options = ["-D", "1", "-N", "5"]
search = attribute_selection.ASSearch(classname=cname, options=options)
self.assertIsNotNone(search, msg="Search should not be None: " + cname + "/" + str(options))
cname = "weka.attributeSelection.CfsSubsetEval"
options = ["-P", "1", "-E", "1"]
evaluation = attribute_selection.ASEvaluation(classname=cname, options=options)
self.assertIsNotNone(evaluation, msg="Evaluation should not be None: " + cname + "/" + str(options))
attsel = attribute_selection.AttributeSelection()
self.assertIsNotNone(search, msg="AttributeSelection should not be None!")
attsel.search(search)
attsel.evaluator(evaluation)
attsel.select_attributes(data)
self.assertEqual(9, attsel.number_attributes_selected, msg="number_attributes_selected differs")
self.assertEqual([0, 4, 8, 11, 12, 19, 24, 32, 33, 38], attsel.selected_attributes.tolist(), msg="selected_attributes differ")
self.assertGreater(len(attsel.results_string), 0, msg="results_string should get produced")
def test_attributeselectedclassifier(self):
"""
Tests the AttributeSelectedClassifier class.
"""
asc = classifiers.AttributeSelectedClassifier()
asc.evaluator = attsel.ASEvaluation(classname="weka.attributeSelection.CfsSubsetEval", options=["-P", "1", "-E", "1"])
asc.search = attsel.ASSearch(classname="weka.attributeSelection.GreedyStepwise", options=["-B", "-T", "-1.7E308", "-N", "-1", "-num-slots", "1"])
self.assertEqual("weka.attributeSelection.CfsSubsetEval -P 1 -E 1", asc.evaluator.to_commandline(), msg="evaluator command-lines differs")
self.assertEqual("weka.attributeSelection.GreedyStepwise -B -T -1.7E308 -N -1 -num-slots 1", asc.search.to_commandline(), msg="search command-lines differs")
def test_capabilities(self):
"""
Tests the capabilities.
"""
cname = "weka.attributeSelection.CfsSubsetEval"
options = ["-P", "1", "-E", "1"]
evaluation = attribute_selection.ASEvaluation(classname=cname, options=options)
self.assertIsNotNone(evaluation, msg="Evaluation should not be None: " + cname + "/" + str(options))
self.assertEqual(cname, evaluation.classname, msg="Classnames differ!")
caps = evaluation.capabilities
self.assertIsNotNone(caps, msg="Capabilities are None!")
