Naive Bayesian scores tend to be over confident so it can be difficult to calibrate what exactly they mean in terms of probability.
Sent from my iPhone On Jan 28, 2012, at 14:19, Lance Norskog <[email protected]> wrote: > What algebra can be done on the classification scores? For example: > > Classification of A : 60% > Classification of B: 80% > A and B are correct: ? > A or B are correct: ? > > Of course these exist for probabilities but I have not found handy > formulae. Do these forumulae even exist with log-likelihood? > > On Sat, Jan 28, 2012 at 12:36 PM, Ted Dunning <[email protected]> wrote: >> It always tells you the most likely category, but you can redefine the >> output to only trigger if the most likely category really dominates the >> results. >> >> With two categories, this is reasonable. For a dozen it is much more >> debatable. >> >> This works with the SGD classifiers as well and I have seen this used in a >> multi-level classifier. >> >> On Fri, Jan 27, 2012 at 8:06 PM, Stuart Smith <[email protected]> wrote: >> >>> Hello, >>> >>> Does naive bayes always classify a document into a category? >>> Or will it refuse to classify something it cannot? >>> > > > > -- > Lance Norskog > [email protected]
