Changeset 7565:8866770eaf2e in orange
 Timestamp:
 02/04/11 22:51:40 (3 years ago)
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 default
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 989abbcdc78ab2ffa1f7af018641b512afec37db
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orange/Orange/classification/bayes.py
r7541 r7565 9 9 ********************** 10 10 11 The most primitive bayesian classifier is :obj:`NaiveLearner` 12 (http://en.wikipedia.org/wiki/Naive_Bayes_classifier). 13 The class estimates conditional probabilities from training data and uses them 14 for classification of new data instances. 15 16 Example (`bayesrun.py`_, uses `iris.tab`_) 11 The most primitive Bayesian classifier is :obj:`NaiveLearner`. 12 `Naive Bayes classification algorithm <http://en.wikipedia.org/wiki/Naive_Bayes_classifier>`_ 13 estimates conditional probabilities from training data and uses them 14 for classification of new data instances (`bayesrun.py`_, uses `iris.tab`_): 17 15 18 16 .. literalinclude:: code/bayesrun.py 19 17 :lines: 7 20 18 21 19 .. index:: Naive Bayesian Learner … … 30 28 Examples 31 29 ======== 32 NaiveLearner can estimate probabilities using relative frequencies or 33 mestimate. 34 35 Example (`bayesmestimate.py`_, uses `lenses.tab`_) 30 :obj:`NaiveLearner` can estimate probabilities using relative frequencies or 31 mestimate (`bayesmestimate.py`_, uses `lenses.tab`_): 36 32 37 33 .. literalinclude:: code/bayesmestimate.py … … 41 37 shift towards the second class  as compared to probabilities above, where 42 38 relative frequencies were used. Note that the change in error estimation did 43 not have any effect on apriori 44 probabilities. 45 46 Example (`bayesthresholdAdjustment.py`_, uses `adultsample.tab`_) 39 not have any effect on apriori probabilities 40 (`bayesthresholdAdjustment.py`_, uses `adultsample.tab`_): 47 41 48 42 .. literalinclude:: code/bayesthresholdAdjustment.py
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