Probability Returning Infinity for most Categories

[Nath5]

Hello,

I know you haven't worked on this in a while but was wondering if you had any idea why I keep seeing this issue. I have added about 25 categories to the model with lots of data in each category. For the majority of the categories no matter what I feed in when I classify a chunk of text most of the categories return a probability of infinity.

ex.

Classification[
category=friends_gatherings,
probability=Infinity,
featureset=[
after,
school,
soccerabout,
this,
...
--
]
]

[allenanie]

I literally encountered the same issue LOL. I think it may be because he didn't do any smoothing technique.

[ptnplanet]

Hello, yes, unfortunately there is no smoothing technique applied. PROD(P(featI|cat) becomes pretty big with lots of features and categories. You can however provide your own IFeatureProbability<T, K> calculator. This requires you to provide an own Classifier<T, K> though (or to override featuresProbabilityProduct(Collection<T> features, K category) in BayesClassifier<T, K>.

[ptnplanet]

Hi all. You might want to explore the latest feature branch (feature/weight).

Take the feature weight into consideration when calculating the featureProbabilityProduct

• Made BayesClassifier.featureProbabilityProduct public to enable other
  implementations to overwrite the calculation
• By default now take the feature weight and the assumed Probability
  into consideration when calculating the feautersProbabilityProduct
• Added a test to test with high number of categories

[barovehicles]

I'm comparing the results in python with numpy and the results with this routine and are completely different. This routine definitely don't work.