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FP-Growth is a recursive mining algorithm for frequent patterns. With each recursion, a new FP-tree and the corresponding header table are built. This paper proposes another approach to improve the mining efficiency: only one FP-tree is constructed, and instead of building new trees in every recursion, builds new header tables; frequent patterns are generated along the way, so we call this algorithm â€œheader table recursion (HTR)â€� method. Tests show that it will get better performance for rel
fp_growth implements the FP-Growth algorithm for Frequent Itemset Mining. It uses an extended prefix-tree (FP-tree) structure to store the database in a compressed form. FP-growth adopts a divide-and-conquer approach to decompose both the mining tasks and the databases. Reference: 1. http://en.wikipedia.org/wiki/Association_rule_learning 2. Jiawei Han, Jian Pei and Yiwen Yin. Mining Frequent Patterns without Candidate Generation. ACM SIGMOD, 2000.
PHP file-based B+tree index, integrated in flatpress (http://www.flatpress.org) source code is currently available at http://flatpress.svn.sourceforge.net/viewvc/flatpress/trunk/flatpress/fp-includes/core/core.bplustree.class.php?view=log
A personal wardrobe consultant which keeps track of the clothes you have in your closet and helps you to choose them day by day, always suggesting the most stylish and creative combinations. Runs on J2ME enabled devices supporting CLDC 1.1, MIDP 2.0
OverviewKiama is a Scala library for language processing. It enables convenient analysis and transformation of structured data. The programming styles supported by the library are based on well-known formal language processing paradigms, including attribute grammars, tree rewriting, abstract state machines, and pretty printing. Kiama is a project of the Programming Languages Research Group in the Department of Computing at Macquarie University and is led by Tony Sloane (inkytonik on GMail and Tw
Warning*.py files are easily modifiable BUT you need some python modules that are available on : https://code.google.com/p/autiwa-py-modules/ AimIntroduction of fortran 90 modules, modification of arguments. The aim is to keep the original behaviour of mercury. The present code must respect : Fully compatible with mercury configuration files (param.in, big.in, small.in and so on) MUST return exactly the same results than the original 'mercury' binaries. A python script has been made to be sure o