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Project Summary

# Project Name: nbc
# Authiors : T.S.Yo and S. Sinha
# Last Updated: 2005.11.11

# Description:
  An implementation of Naive Bayes Classifier in S-language, tested under S-PLUS.

# Correction 2005.11.11:
In nb.train() we privously use Pr(Ai,C) instead of Pr(Ai|C), this
problem is fixed in this version.

# ./src/

File Name Description
----------------- ----------------------------------------------------
NB_functions.ssc A S-Plus™ Script file contains the developed
                    functions, nb.train and nb.ptrdict. Executingthis
                    script will install these two functions as objects.
                    
RunTest.ssc A S-Plus™ Script file to read in the WSBC data set
                    and perform a single test. Executing this script
                    will create a data frame bcdata, a naive Bayes model
                    nb using the first 400 records, and a prediction
                    object pred using the later 283 records.

bc.data The WSBC data set. The values “?” in the original
                    database are replaced by NA (missing).

RunBootstrap.ssc A S-Plus™ Script file to read in the WSBC data set
                    and perform a L=100 bootstrapping experiment.
                    (This script will run for a very long time!)

RunCV.ssc A S-Plus™ Script file to perform a 5-fold cross
                    -validation experiment. Executing this script will
                    create a list object cvcfm contains the confusion
                    matrix for each fold, and an array cverr to hold the
                    five error rates.
----------------- ----------------------------------------------------
 

# Procedure to install and test the developed functions
    First, unzip the files in appendixA.zip into the working directory.
    For installation, execute the NB_functions.ssc.
    After installation, execute the RunTest.ssc to test the functions.
    After the installation of the function, both RunBootstrap.ssc and
    RunCV.ssc can be executed for further testing.

Tags

classifier machinelearning naivebayes slanguage s-plus statistics

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