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File Date Author Commit
 letter-FIJ-demo 2010-01-12 scheaman@fpga1.ucsd.edu scheaman@fpga1.ucsd.edu [443c2b] jboost-2.0r8.4
 README 2010-01-12 scheaman@fpga1.ucsd.edu scheaman@fpga1.ucsd.edu [443c2b] jboost-2.0r8.4
 long.spec 2010-01-12 scheaman@fpga1.ucsd.edu scheaman@fpga1.ucsd.edu [443c2b] jboost-2.0r8.4
 long.test 2010-01-12 scheaman@fpga1.ucsd.edu scheaman@fpga1.ucsd.edu [443c2b] jboost-2.0r8.4
 long.train 2010-01-12 scheaman@fpga1.ucsd.edu scheaman@fpga1.ucsd.edu [443c2b] jboost-2.0r8.4
 noisy_line.output.tree 2010-11-03 scheaman scheaman [bc7321] updated to 2.2
 noisy_line.spec 2010-01-12 scheaman@fpga1.ucsd.edu scheaman@fpga1.ucsd.edu [443c2b] jboost-2.0r8.4
 noisy_line.test 2010-01-12 scheaman@fpga1.ucsd.edu scheaman@fpga1.ucsd.edu [443c2b] jboost-2.0r8.4
 noisy_line.train 2010-01-12 scheaman@fpga1.ucsd.edu scheaman@fpga1.ucsd.edu [443c2b] jboost-2.0r8.4
 run_demo.sh 2010-01-12 scheaman@fpga1.ucsd.edu scheaman@fpga1.ucsd.edu [443c2b] jboost-2.0r8.4
 spambase.data 2010-01-12 scheaman@fpga1.ucsd.edu scheaman@fpga1.ucsd.edu [443c2b] jboost-2.0r8.4
 spambase.spec 2010-01-12 scheaman@fpga1.ucsd.edu scheaman@fpga1.ucsd.edu [443c2b] jboost-2.0r8.4
 spambase.test 2010-01-12 scheaman@fpga1.ucsd.edu scheaman@fpga1.ucsd.edu [443c2b] jboost-2.0r8.4
 spambase.train 2010-01-12 scheaman@fpga1.ucsd.edu scheaman@fpga1.ucsd.edu [443c2b] jboost-2.0r8.4

Read Me

These files are for testing JBoost.  Below is a brief description
of the datasets.

--------------------------
UCI FILES

Original files for letter and spambase can be obtained from the UCI
Machine Learning repository: http://www.ics.uci.edu/~mlearn/MLSummary.html

For documentation, see
  * http://www.ics.uci.edu/~mlearn/databases/spambase/spambase.DOCUMENTATION
  * ftp://ftp.ics.uci.edu/pub/machine-learning-databases/spambase/spambase.names


---------------------------
Noisy Line

The noisy line dataset is an artificial construction to test
BrownBoost's resistance to noisy data.  The function that generated
the training set is:
          
         +1    if x < .5  (w/prob 90%)
  f(x) = 
         -1    if x > .5  (w/prob 90%)

The test set is the deterministic version of the function
          
         +1    if x < .5
  f(x) = 
         -1    if x > .5


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