from scipy.io import arff
import pysubgroup as ps
import pandas as pd
data = pd.DataFrame(arff.loadarff("../data/credit-g.arff")[0])
target = ps.NominalTarget('class', b'bad')
searchSpace = ps.createNominalSelectors(data, ignore=['class'])
task = ps.SubgroupDiscoveryTask(data,
target,
searchSpace,
resultSetSize=10,
depth=3,
qf=ps.StandardQF(1.0))
result = ps.BeamSearch(beamWidth=10).execute(task)
for (q, sg) in result:
print(str(q) + ":\t" + str(sg.subgroupDescription))
print("******")
result = ps.SimpleDFS().execute(task)
for (q, sg) in result:
print(str(q) + ":\t" + str(sg.subgroupDescription))
# print WRAccQF().evaluateFromDataset(data, Subgroup(target, []))
def test_BeamSearch(self):
self.runAlgorithm(ps.BeamSearch(beam_width=12), "BeamSearch",
self.result, self.qualities, self.task)
def test_BeamSearch_sum(self):
self.task.qf = ps.CountCallsInterestingMeasure(
ps.StandardQFNumeric(self.task.qf.a, False, 'sum'))
self.runAlgorithm(ps.BeamSearch(), "BeamSearch sum", self.result,
self.qualities, self.task)
import pysubgroup as ps
import pandas as pd
data = pd.read_table("../data/titanic.csv")
target = ps.NominalTarget('Survived', True)
searchspace = ps.create_selectors(data, ignore=['Survived'])
task = ps.SubgroupDiscoveryTask(data,
target,
searchspace,
result_set_size=5,
depth=2,
qf=ps.ChiSquaredQF())
result = ps.BeamSearch().execute(task)
for (q, sg) in result:
print(str(q) + ":\t" + str(sg.subgroup_description))
def test_BeamSearch(self):
self.task.qf = ps.CountCallsInterestingMeasure(ps.PredictionQFNumeric(self.task.qf.a, False))
self.runAlgorithm(ps.BeamSearch(), "BeamSearch sum", self.result, self.qualities, self.task)
