def __init__(self, dataSet: DataSet):
"""
Constructor for normalize feature filter. It calculates and stores the mean (m) and standard deviation (s) of
the sample.
PARAMETERS
----------
dataSet : DataSet
Instances whose continuous attribute values will be normalized.
"""
super().__init__(dataSet)
self.__averageInstance = dataSet.getInstanceList().average()
self.__standardDeviationInstance = dataSet.getInstanceList(
).standardDeviation()
def generate(self) -> DataSet:
"""
Creates a dataset from the treeBank. Calls generateInstanceListFromTree for each parse tree in the treebank.
RETURNS
-------
DataSet
Created dataset.
"""
dataSet = DataSet()
for i in range(self.__treeBank.size()):
parseTree = self.__treeBank.get(i)
dataSet.addInstanceList(
self.generateInstanceListFromTree(parseTree))
return dataSet
def generate(self) -> DataSet:
"""
Creates a dataset from the corpus. Calls generateInstanceFromSentence for each parse sentence in the corpus.
RETURNS
-------
DataSet
Created dataset.
"""
dataSet = DataSet()
for sentence in self.__corpus.sentences:
for j in range(sentence.wordCount()):
generatedInstance = self.instanceGenerator.generateInstanceFromSentence(
sentence, j)
if generatedInstance is not None:
dataSet.addInstance(generatedInstance)
return dataSet
def setUp(self) -> None:
attributeTypes = 4 * [AttributeType.CONTINUOUS]
dataDefinition = DataDefinition(attributeTypes)
self.iris = DataSet(dataDefinition, ",", "../../datasets/iris.data")
attributeTypes = 6 * [AttributeType.CONTINUOUS]
dataDefinition = DataDefinition(attributeTypes)
self.bupa = DataSet(dataDefinition, ",", "../../datasets/bupa.data")
attributeTypes = 34 * [AttributeType.CONTINUOUS]
dataDefinition = DataDefinition(attributeTypes)
self.dermatology = DataSet(dataDefinition, ",",
"../../datasets/dermatology.data")
attributeTypes = 6 * [AttributeType.DISCRETE]
dataDefinition = DataDefinition(attributeTypes)
self.car = DataSet(dataDefinition, ",", "../../datasets/car.data")
attributeTypes = 9 * [AttributeType.DISCRETE]
dataDefinition = DataDefinition(attributeTypes)
self.tictactoe = DataSet(dataDefinition, ",",
"../../datasets/tictactoe.data")
attributeTypes = 8 * [AttributeType.DISCRETE]
dataDefinition = DataDefinition(attributeTypes)
self.nursery = DataSet(dataDefinition, ",",
"../../datasets/nursery.data")
attributeTypes = []
for i in range(6):
if i % 2 == 0:
attributeTypes.append(AttributeType.DISCRETE)
else:
attributeTypes.append(AttributeType.CONTINUOUS)
dataDefinition = DataDefinition(attributeTypes)
self.chess = DataSet(dataDefinition, ",", "../../datasets/chess.data")
def __init__(self, dataSet: DataSet):
"""
Constructor that sets the dataSet and all the attributes distributions.
PARAMETERS
----------
dataSet : DataSet
DataSet that will bu used.
"""
super().__init__(dataSet)
self.attributeDistributions = dataSet.getInstanceList(
).allAttributesDistribution()
class DataSetTest(unittest.TestCase):
iris: DataSet
bupa: DataSet
dermatology: DataSet
car: DataSet
tictactoe: DataSet
nursery: DataSet
chess: DataSet
def setUp(self):
attributeTypes = 4 * [AttributeType.CONTINUOUS]
dataDefinition = DataDefinition(attributeTypes)
self.iris = DataSet(dataDefinition, ",", "../../datasets/iris.data")
attributeTypes = 6 * [AttributeType.CONTINUOUS]
dataDefinition = DataDefinition(attributeTypes)
self.bupa = DataSet(dataDefinition, ",", "../../datasets/bupa.data")
attributeTypes = 34 * [AttributeType.CONTINUOUS]
dataDefinition = DataDefinition(attributeTypes)
self.dermatology = DataSet(dataDefinition, ",",
"../../datasets/dermatology.data")
attributeTypes = 6 * [AttributeType.DISCRETE]
dataDefinition = DataDefinition(attributeTypes)
self.car = DataSet(dataDefinition, ",", "../../datasets/car.data")
attributeTypes = 9 * [AttributeType.DISCRETE]
dataDefinition = DataDefinition(attributeTypes)
self.tictactoe = DataSet(dataDefinition, ",",
"../../datasets/tictactoe.data")
attributeTypes = 8 * [AttributeType.DISCRETE]
dataDefinition = DataDefinition(attributeTypes)
self.nursery = DataSet(dataDefinition, ",",
"../../datasets/nursery.data")
attributeTypes = []
for i in range(6):
if i % 2 == 0:
attributeTypes.append(AttributeType.DISCRETE)
else:
attributeTypes.append(AttributeType.CONTINUOUS)
dataDefinition = DataDefinition(attributeTypes)
self.chess = DataSet(dataDefinition, ",", "../../datasets/chess.data")
def test_SampleSize(self):
self.assertEquals(150, self.iris.sampleSize())
self.assertEquals(345, self.bupa.sampleSize())
self.assertEquals(366, self.dermatology.sampleSize())
self.assertEquals(1728, self.car.sampleSize())
self.assertEquals(958, self.tictactoe.sampleSize())
self.assertEquals(12960, self.nursery.sampleSize())
self.assertEquals(28056, self.chess.sampleSize())
def test_ClassCount(self):
self.assertEquals(3, self.iris.classCount())
self.assertEquals(2, self.bupa.classCount())
self.assertEquals(6, self.dermatology.classCount())
self.assertEquals(4, self.car.classCount())
self.assertEquals(2, self.tictactoe.classCount())
self.assertEquals(5, self.nursery.classCount())
self.assertEquals(18, self.chess.classCount())
def test_GetClasses(self):
self.assertEquals("Iris-setosa;Iris-versicolor;Iris-virginica",
self.iris.getClasses())
self.assertEquals("1;2", self.bupa.getClasses())
self.assertEquals("2;1;3;5;4;6", self.dermatology.getClasses())
self.assertEquals("unacc;acc;vgood;good", self.car.getClasses())
self.assertEquals("positive;negative", self.tictactoe.getClasses())
self.assertEquals("recommend;priority;not_recom;very_recom;spec_prior",
self.nursery.getClasses())
self.assertEquals(
"draw;zero;one;two;three;four;five;six;seven;eight;nine;ten;eleven;twelve;thirteen;fourteen;fifteen;sixteen",
self.chess.getClasses())