def setUp(self):
# Using example from https://en.wikipedia.org/wiki/Naive_Bayes_classifier
# height (feet), weight (lbs), foot size (inches)
self.xs = [
[6, 180, 12],
[5.92, 190, 11],
[5.58, 170, 12],
[5.92, 165, 10],
[5, 100, 6],
[5.5, 150, 8],
[5.42, 130, 7],
[5.75, 150, 9],
]
self.ys = [
'male',
'male',
'male',
'male',
'female',
'female',
'female',
'female',
]
self.model = NaiveBayes.train(self.xs, self.ys)
self.test = [6, 130, 8]
def test_car_data(self):
"""Simple example using car data."""
# Car data from example 'Naive Bayes Classifier example'
# by Eric Meisner November 22, 2003
# http://www.inf.u-szeged.hu/~ormandi/teaching/mi2/02-naiveBayes-example.pdf
xcar = [
["Red", "Sports", "Domestic"],
["Red", "Sports", "Domestic"],
["Red", "Sports", "Domestic"],
["Yellow", "Sports", "Domestic"],
["Yellow", "Sports", "Imported"],
["Yellow", "SUV", "Imported"],
["Yellow", "SUV", "Imported"],
["Yellow", "SUV", "Domestic"],
["Red", "SUV", "Imported"],
["Red", "Sports", "Imported"],
]
ycar = [
"Yes",
"No",
"Yes",
"No",
"Yes",
"No",
"Yes",
"No",
"No",
"Yes",
]
carmodel = NaiveBayes.train(xcar, ycar)
self.assertEqual("Yes", NaiveBayes.classify(carmodel, ["Red", "Sports", "Domestic"]))
self.assertEqual("No", NaiveBayes.classify(carmodel, ["Red", "SUV", "Domestic"]))
def setUp(self):
# Using example from https://en.wikipedia.org/wiki/Naive_Bayes_classifier
# height (feet), weight (lbs), foot size (inches)
self.xs = [
[6, 180, 12],
[5.92, 190, 11],
[5.58, 170, 12],
[5.92, 165, 10],
[5, 100, 6],
[5.5, 150, 8],
[5.42, 130, 7],
[5.75, 150, 9],
]
self.ys = [
'male',
'male',
'male',
'male',
'female',
'female',
'female',
'female',
]
self.model = NaiveBayes.train(self.xs, self.ys)
self.test = [6, 130, 8]
def test_car_data(self):
"""Simple example using car data."""
# Car data from example 'Naive Bayes Classifier example'
# by Eric Meisner November 22, 2003
# http://www.inf.u-szeged.hu/~ormandi/teaching/mi2/02-naiveBayes-example.pdf
xcar = [
['Red', 'Sports', 'Domestic'],
['Red', 'Sports', 'Domestic'],
['Red', 'Sports', 'Domestic'],
['Yellow', 'Sports', 'Domestic'],
['Yellow', 'Sports', 'Imported'],
['Yellow', 'SUV', 'Imported'],
['Yellow', 'SUV', 'Imported'],
['Yellow', 'SUV', 'Domestic'],
['Red', 'SUV', 'Imported'],
['Red', 'Sports', 'Imported'],
]
ycar = [
'Yes',
'No',
'Yes',
'No',
'Yes',
'No',
'Yes',
'No',
'No',
'Yes',
]
carmodel = NaiveBayes.train(xcar, ycar)
self.assertEqual("Yes", NaiveBayes.classify(carmodel, ['Red', 'Sports', 'Domestic']))
self.assertEqual("No", NaiveBayes.classify(carmodel, ['Red', 'SUV', 'Domestic']))
def test_train_function_with_priors(self):
model = NaiveBayes.train(self.xs,
self.ys,
priors={
'male': 0.1,
'female': 0.9
})
result = NaiveBayes.calculate(model, self.test, scale=True)
expected = -692.0
self.assertEqual(expected, round(result['male']))
def test_train_function_with_priors(self):
model = NaiveBayes.train(self.xs, self.ys, priors={'male': 0.1, 'female': 0.9})
result = NaiveBayes.calculate(model, self.test, scale=True)
expected = -692.0
self.assertEqual(expected, round(result['male']))
def bayes(self): xs = [[-53.0, -200.78], [117.0, -267.14], [57.0, -163.47], [16.0, -190.3], [11.0, -220.94], [85.0, -193.94], [16.0, -182.71], [15.0, -180.41], [-26.0, -181.73], [58.0, -259.87], [126.0, -414.53], [191.0, -249.57], [113.0, -265.28], [145.0, -312.99], [154.0, -213.83], [147.0, -380.85], [93.0, -291.13]] ys =[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0] model = NaiveBayes.train(xs,ys) return model
