The pboost toolbox is a set of command line programs and a Matlab wrapper for mining frequent subsequences and sequence classification. For our purposes, a sequence is defined an ordered sequence of sets of discrete numbers. (If all sets contain exactly one element, the sequence is a string. If there is only one set, it reduces to itemset mining.) This definition of sequence is flexible enough to model a number of interesting problems and has been used successfully for human action classification in video data and web clickstream mining.
The pboost toolbox includes source codes for the following functionalities:
* PrefixSpan frequent subsequence mining (frequency defined either by minimum support threshold or by top-K frequent subsequences) * Discriminative subsequence mining * nu-LPBoost 2-class classifier * nu-LPBoost 1.5-class (one class with negative examples) classifier * DDAG-decomposition multiclass classifier * Matlab wrappers to all of the above functionality, as well as glue code to the gboost toolbox.
- Changes to previous version:
Initial Announcement on mloss.org.
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