def compareNoisyMaxSimple():
"""
Network CancerMax_simple 10k
"""
real = (
(('Malignant', 'Smoker', 'TwoPacks'), 0.23),
(('Malignant', 'Smoker', 'OnePack'), 0.11),
(('Malignant', 'Genetic', 'True'), 0.25),
(('Benign', 'Smoker', 'TwoPacks'), 0.25),
(('Benign', 'Smoker', 'OnePack'), 0.14),
(('Benign', 'Genetic', 'True'), 0.55),
)
b1 = BayesianDataSet("../data/MAX/CancerMAX_simple10k.txt")
print b1
b1.addChildNode(2,'No', [0,1], ['False', 'False'])
print "COUNTED"
for p in b1.countForChild(2):
print p
print "SOLVED"
for p in b1.solveForChild(2):
print p
print "REAL"
for p in real:
print p
def compareNoisyMAX():
"""
Network CancerMax 20k records
"""
real = (
(('Malignant', 'Smoker', 'TwoPacks'), 0.23),
(('Malignant', 'Smoker', 'OnePack'), 0.11),
(('Malignant', 'Genetic', 'True'), 0.25),
(('Malignant', 'CoalWorker', 'True'), 0.15),
(('Malignant', 'BadDiet', 'Good'), 0.04),
(('Malignant', 'BadDiet', 'Bad'), 0.13),
(('Benign', 'Smoker', 'TwoPacks'), 0.25),
(('Benign', 'Smoker', 'OnePack'), 0.14),
(('Benign', 'Genetic', 'True'), 0.55),
(('Benign', 'CoalWorker', 'True'), 0.66),
(('Benign', 'BadDiet', 'Good'), 0.63),
(('Benign', 'BadDiet', 'Bad'), 0.22),
)
b1 = BayesianDataSet("../data/MAX/CancerMAX5k.txt")
print b1
b1.addChildNode(4,'No', [0,1,2,3], ['False', 'False', 'False', 'Medium'])
print "COUNTED"
for p in b1.countForChild(4):
print p
print "SOLVED"
for p in b1.solveForChild(4):
print p
print "REAL"
for p in real:
print p
def compareNoisyOR():
"""
Network CancerOR 10k records
"""
real = (
(('True', 'Smoker', 'True'), 0.61),
(('True', 'Genetic', 'True'), 0.25),
(('True', 'CoalWorker', 'True'), 0.15),
(('True', 'BadDiet', 'True'), 0.04),
)
b1 = BayesianDataSet("../data/5n/10k/Network1.txt")
b1.addChildNode(4,'False', [0,1,2,3], ['False', 'False', 'False', 'False'])
print "COUNTED"
for p in b1.countForChild(4):
print p
print "SOLVED"
for p in b1.solveForChild(4):
print p
print "REAL"
for p in real:
print p