COMMITTEE_LNK(1)

NAME
committee_lnk - Committee Classifier

SYNOPSIS
Program for testing a committee classifier.

committee_lnk [-class_type n] [-cvtest]
[-classifier_options]

EXAMPLE
# Create three mlp error files by running the next two
# commands three times, changing the random number seed
# and the error file name each time.
foreach num (0 1 2)
> mlp -train -create -nodes 2,25,10 -epochs 100 \
-fparam mlp$num.param -pathdata $LNKHOME/data/class \
-finput vowel.train -fdescribe vowel.defaults \
-npatterns 338 -seed $num
> mlp -pathdata $LNKHOME/data/class -finput vowel.test \
-fdescribe vowel.defaults -fparam mlp$num.param -verror 2 \
-npatterns 167 -ferror mlp$num.err
end

# Create a committee data file
err2data -file_list mlp0.err,mlp1.err,mlp2.err \
-noutputs 10 -output_file vowel_comm.test

# Run the committee classifier
committee_lnk -class_type 0 -pathdata $LNKHOME/data/class \
-finput vowel_comm.test -fdescribe vowel_comm.defaults \
-npatterns 166

DESCRIPTION
There is no training for this classifier. In cross validation, no training is done but testing is performed for each cross validation test fold. In order for the patterns to be assigned to the same folds they would be for other classifiers, the patterns in the error file must be sorted by their pattern numbers before presentation to the classifier. In testing, there is no need to specify a classifier parameter file, since no training parameters are used.

There are three testing algorithms. In the first, averaging, the output for each class is an average of the outputs from each classifier for that class. In the second algorithm, taking the medians, the outputs are the medians of the classifier class outputs. In the third algorithm, each classifier votes for the class it selected (the class with the highest output of the N outputs). The class with the most votes is selected by the committee classifier. The testing algorithm is selected using the class_type flag.

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

-class_vote n
    n determines the testing algorithm.

    0 Average
        Average the outputs for each class to find the committee classifier outputs.

    1 Median
        Find the median output for each class to find the committee classifier outputs.

    2 Vote
        Each classifier in the committee votes for its highest class. The class returned by the committee classifier is the class with the most votes.

-classifier_options
    committee_lnk accepts the general classifier arguments described on the classifier(1) manual page. Certain arguments are not used by the program, and so are not available.

    Unavailable arguments from general list:

    -adjust_test_priors -test_priors_list -test_uniform_priors

    -adjust_train_priors -train_priors_list -train_uniform_priors -priors_npatterns
        The committee classifier does not train and so cannot adjust training priors.

    -train -fparam
        The committee classifier does not train and writes no parameter files.

    -ninputs -features -normalize -fnorm.
        Feature selection and normalization are not permitted.

SEE ALSO
classifier(1)

HISTORY
First written 10 August 1994 by Linda Kukolich

Modified 19 April 1995, completed example, adding how to create a committee data file. Added that cross validation is available.

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