Class NaiveBayesModel
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object --+
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NaiveBayesModel
Model for Naive Bayes classifiers.
Contains two parameters:
- pi: vector of logs of class priors (dimension C)
- theta: matrix of logs of class conditional probabilities (CxD)
>>> data = [
... LabeledPoint(0.0, [0.0, 0.0]),
... LabeledPoint(0.0, [0.0, 1.0]),
... LabeledPoint(1.0, [1.0, 0.0]),
... ]
>>> model = NaiveBayes.train(sc.parallelize(data))
>>> model.predict(array([0.0, 1.0]))
0.0
>>> model.predict(array([1.0, 0.0]))
1.0
>>> sparse_data = [
... LabeledPoint(0.0, SparseVector(2, {1: 0.0})),
... LabeledPoint(0.0, SparseVector(2, {1: 1.0})),
... LabeledPoint(1.0, SparseVector(2, {0: 1.0}))
... ]
>>> model = NaiveBayes.train(sc.parallelize(sparse_data))
>>> model.predict(SparseVector(2, {1: 1.0}))
0.0
>>> model.predict(SparseVector(2, {0: 1.0}))
1.0
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__init__(self,
labels,
pi,
theta)
x.__init__(...) initializes x; see help(type(x)) for signature |
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predict(self,
x)
Return the most likely class for a data vector x |
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Inherited from object:
__delattr__,
__format__,
__getattribute__,
__hash__,
__new__,
__reduce__,
__reduce_ex__,
__repr__,
__setattr__,
__sizeof__,
__str__,
__subclasshook__
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Inherited from object:
__class__
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__init__(self,
labels,
pi,
theta)
(Constructor)
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x.__init__(...) initializes x; see help(type(x)) for signature
- Overrides:
object.__init__
- (inherited documentation)
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