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Description
Interface Summary  

ArithCodeModel  Interface for an adaptive statistical model of a stream to be used as a basis for arithmetic coding and decoding. 
Class Summary  

AdaptiveUnigramModel  Provides an adaptive model based on bytes observed in the input stream. 
ArithCodeInputStream  An input stream which uses a statistical model and arithmetic coding for decompression of encoded bytes read from an underlying input stream. 
ArithCodeOutputStream  A filter output stream which uses a statistical model and arithmetic coding for compression of bytes read from an underlying arithmetic encoder. 
ArithDecoder  Performs arithmetic decoding, converting bit input into cumulative probability interval output. 
ArithEncoder  Performs arithmetic encoding, converting cumulative probability interval input into bit output. 
BitInput  Reads input from an underlying input stream a bit at a time. 
BitOutput  Writes to an underlying output stream a bit at a time. 
ByteBuffer  Stores a queue of bytes in a buffer with a maximum size. 
ByteSet  A set of bytes. 
CompressionCategorizer  Recent results in bioinformatics and observations about the Kolmogorov complexity seem to suggest that simple classification systems can be built using offtheshelf compression algorithms. 
ExcludingAdaptiveUnigramModel  Package class for use by the PPMModel. 
PPMCompress  Commandline function for compressing files or streams. 
PPMDecompress  Commandline function for decompressing files or streams. 
PPMModel  Provides a cumulative, adaptive byte model implementing prediction by partial matching up to a specified maximum context size. 
PPMNode  A node in a depthbounded suffix tree that represents counts of sequences of bytes. 
Test  Runs test suite for arithmetic coding and decoding with all of th esupplied
compression models from Test.main(java.lang.String[]) . 
TestSet  Package local helper class to compute statistics for a set of compression experiments. 
TestStatistics  Package local helper class to compute statistics for a single compression experiment. 
UniformModel  A singleton uniform distribution byte model. 
Implementation of the compressionbased classification technique described in
the papers "Towards
ParameterFree Data Mining" and "The Similarity
Metric", respectivelly by Ming Li and Keogh et al. It can use both the Zip compression algorithm available with the Java SDK, or a more
efficient arithmethic coding compressor.
Arithmetic coding is a general technique for coding the outcome of a stochastic process based
on an adaptive model. The expected bit rate is the crossentropy rate of the model versus the
actual process. PPM, prediction by partial matching, is an adaptive statistical model of a
symbol sequence which models the likelihood of the next byte based on a (relatively short)
suffix of the sequence of previous bytes.


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