hinduce-associations-apriori: Apriori algorithm for association rule mining
This module provides an implementation of the Apriori algorithm for association rule mining. It uses Control.Parallel.Strategies for parallelism and allows the user to provide custom selection criteria. See hinduce-examples for an example. hInduce is a framework for knowledge discoverymachine learningdata mining. It has a modular design that hopefully will invite others to re-use and build upon the interface. This module currently deviates from this concept, because we had a different focus and too limited time budget to investigate other rule mining algorithms and find any use for this kind of abstraction.
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Versions [RSS] | 0.0.0.0 |
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Dependencies | base (>=4 && <5), containers (>=0.4.2.0), deepseq (>=1.1.0.0), hinduce-missingh (>=0.0.0.0), parallel (>=3.1.0.1), vector (>=0.9.1) [details] |
License | MIT |
Copyright | Hidde Verstoep |
Author | Hidde Verstoep |
Maintainer | none |
Category | Data Mining |
Home page | https://github.com/roberth/hinduce-associations-apriori |
Uploaded | by RobertHensing at 2012-02-07T20:41:16Z |
Distributions | NixOS:0.0.0.0 |
Reverse Dependencies | 2 direct, 0 indirect [details] |
Downloads | 1281 total (7 in the last 30 days) |
Rating | (no votes yet) [estimated by Bayesian average] |
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Status | Docs uploaded by user Build status unknown [no reports yet] |