Пример #1
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    def test_single(self):
        self.assertEqual(classify_normal({'a': 100}, {'A': [{'a': 100}]}), 'A')
        self.assertEqual(
            classify_normal({
                'a': 100,
                'b': 0
            }, {'A': [{
                'a': 100,
                'b': 0
            }]}), 'A')

        self.assertEqual(
            classify_normal({
                'a': 100,
                'b': 0
            }, {
                'A': [{
                    'a': 100,
                    'b': 10
                }],
                'B': [{
                    'a': 50,
                    'b': 100
                }]
            }), None)
Пример #2
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    def test_single(self):
        self.assertEqual(classify_normal({'a': 100}, {'A': [{'a': 100}]}), 'A')
        self.assertEqual(classify_normal({'a': 100, 'b': 0},
                                         {'A': [{'a': 100, 'b': 0}]}), 'A')

        self.assertEqual(classify_normal({'a': 100, 'b': 0},
                                         {'A': [{'a': 100, 'b': 10}],
                                          'B': [{'a': 50, 'b': 100}]}), None)
Пример #3
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 def test_sample(self):
     instance = {'height': 6, 'weight': 130, 'foot size': 8}
     training = {'male': [{'height': 6, 'weight': 180, 'foot size': 12},
                         {'height': 5.92, 'weight': 190, 'foot size': 11},
                         {'height': 5.58, 'weight': 170, 'foot size': 12},
                         {'height': 5.92, 'weight': 165, 'foot size': 10}],
                'female': [{'height': 5, 'weight': 100, 'foot size': 6},
                           {'height': 5.5, 'weight': 150, 'foot size': 8},
                           {'height': 5.42, 'weight': 130, 'foot size': 7},
                           {'height': 5.75, 'weight': 150, 'foot size': 9}]}
     self.assertEqual(classify_normal(instance, training), 'female')
Пример #4
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 def test_basic(self):
     self.assertEqual(
         classify_normal({
             'a': 100,
             'b': 0
         }, {
             'A': [{
                 'a': 100,
                 'b': 10
             }, {
                 'a': 99,
                 'b': -10
             }],
             'B': [{
                 'a': 50,
                 'b': 100
             }, {
                 'a': 70,
                 'b': 90
             }]
         }), 'A')
Пример #5
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 def test_sample(self):
     instance = {'height': 6, 'weight': 130, 'foot size': 8}
     training = {
         'male': [{
             'height': 6,
             'weight': 180,
             'foot size': 12
         }, {
             'height': 5.92,
             'weight': 190,
             'foot size': 11
         }, {
             'height': 5.58,
             'weight': 170,
             'foot size': 12
         }, {
             'height': 5.92,
             'weight': 165,
             'foot size': 10
         }],
         'female': [{
             'height': 5,
             'weight': 100,
             'foot size': 6
         }, {
             'height': 5.5,
             'weight': 150,
             'foot size': 8
         }, {
             'height': 5.42,
             'weight': 130,
             'foot size': 7
         }, {
             'height': 5.75,
             'weight': 150,
             'foot size': 9
         }]
     }
     self.assertEqual(classify_normal(instance, training), 'female')
Пример #6
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 classify_normal({
     'height': 6,
     'weight': 130,
     'foot size': 8
 }, {
     'male': [{
         'height': 6,
         'weight': 180,
         'foot size': 12
     }, {
         'height': 5.92,
         'weight': 190,
         'foot size': 11
     }, {
         'height': 5.58,
         'weight': 170,
         'foot size': 12
     }, {
         'height': 5.92,
         'weight': 165,
         'foot size': 10
     }],
     'female': [{
         'height': 5,
         'weight': 100,
         'foot size': 6
     }, {
         'height': 5.5,
         'weight': 150,
         'foot size': 8
     }, {
         'height': 5.42,
         'weight': 130,
         'foot size': 7
     }, {
         'height': 5.75,
         'weight': 150,
         'foot size': 9
     }]
 }))
Пример #7
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 def test_basic(self):
     self.assertEqual(classify_normal({'a': 100, 'b': 0},
                                      {'A': [{'a': 100, 'b': 10},
                                             {'a': 99, 'b': -10}],
                                       'B': [{'a': 50, 'b': 100},
                                             {'a': 70, 'b':90}]}), 'A')
Пример #8
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import sys
sys.path.append('../')
from bayesian import Bayes, classify_normal, classify

print(' == High Level Functions == ')

print(' -- Gender Classification -- ')
# Decides if the person with those measures is male or female.
print(classify_normal({'height': 6, 'weight': 130, 'foot size': 8},
                      {'male': [{'height': 6, 'weight': 180, 'foot size': 12},
                                {'height': 5.92, 'weight': 190, 'foot size': 11},
                                {'height': 5.58, 'weight': 170, 'foot size': 12},
                                {'height': 5.92, 'weight': 165, 'foot size': 10}],
                       'female': [{'height': 5, 'weight': 100, 'foot size': 6},
                                  {'height': 5.5, 'weight': 150, 'foot size': 8},
                                  {'height': 5.42, 'weight': 130, 'foot size': 7},
                                  {'height': 5.75, 'weight': 150, 'foot size': 9}]}))

print('')

print(' -- Spam Detection With `Classify` -- ')
spams = ["buy viagra", "dear recipient", "meet sexy singles"] # etc
genuines = ["let's meet tomorrow", "remember to buy milk"]
message = "remember the meeting tomorrow"
# Classify as "genuine" because of the words "remember" and "tomorrow".
print(classify(message, {'spam': spams, 'genuine': genuines}))

# Classifies "unknown_file" as either a Python or Java file, considering
# you have directories with examples of each language.
#print classify_file("unknown_file", ["java_files", "python_files"])