NBAYES_AUGMENT(1)

NAME
nbayes_augment - Combine two Naive Bayes classifiers

SYNOPSIS
Program for combining two nbayes classifiers trained on data with the same inputs.

nbayes_augment [ - original_model file ] [ - new_model file ] [ - augmented_model file ] [ - weight x ] [ -ignore_unseen ] ] -unity_laplace ]

EXAMPLE
nbayes_lnk -nbins 4 -train -create -pathdata $LNKHOME/data/class -finput categories.train -fdescribe categories.defaults -fparam nbayes1.param -discrete

nbayes_lnk -nbins 4 -train -create -pathdata $LNKHOME/data/class -finput categories.eval -fdescribe categories.defaults -fparam nbayes2.param -discrete

nbayes_augment -original_model nbayes1.param -new_model nbayes2.param -augmented_model nbayes3.param

DESCRIPTION
Calculates the number of patterns in each bin for the two input classifiers.

OPTIONS
-- Prints a list of all flags and arguments.

-original_model file
    The first model used to create the augmented model.

-new_model file
    The second model used to create the augmented model.

-augmented_model file
    The model to be created by adding together the counts from the original and new models

-weight w
    Counts from each of the models are weighted before being added together to get the counts for the augmented model. The weighting is (1-w)*old_count + w*new_count. Note that this could result in non-integer counts in the resulting model.

-ignore_unseen
    If the original and new models were created with the -ignore_unseen flag set, it needs to be set while calling nbayes_augment. This allows correct calculation of the Laplace correction when deriving the model counts from the log-likelihoods stored in the two parameter files.

-unity_laplace
    If the original and new models were created with the -unity_laplace flag set, it needs to be set while calling nbayes_augment. This allows correct calculation of the Laplace correction when deriving the model counts from the log-likelihoods stored in the two parameter files.

SEE ALSO
nbayes_lnk(1)

HISTORY
First written 2 May 2001 by Linda Kukolich

BUGS
Send bug reports to Linda Kukolich (kukolich@sst.ll.mit.edu)