Cell assembly detection with frequent item set mining
نویسندگان
چکیده
منابع مشابه
Frequent item set mining
Frequent item set mining is one of the best known and most popular data mining methods. Originally developed for market basket analysis, it is used nowadays for almost any task that requires discovering regularities between (nominal) variables. This paper provides an overview of the foundations of frequent item set mining, starting from a definition of the basic notions and the core task. It co...
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In this paper I introduce SaM, a split and merge algorithm for frequent item set mining. Its core advantages are its extremely simple data structure and processing scheme, which not only make it quite easy to implement, but also very convenient to execute on external storage, thus rendering it a highly useful method if the transaction database to mine cannot be loaded into main memory. Furtherm...
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Association rule mining is one of the most important technique in data mining. Which wide range of applications It aims it searching for intersecting relationships among items in large data sets and discovers association rules. The important of association rule mining is increasing with the demand of finding frequent patterns from large data sources. The exploitation of frequent item set has be...
متن کاملComparison of Frequent Item Set Mining Algorithms
Frequent item sets mining plays an important role in association rules mining. Over the years, a variety of algorithms for finding frequent item sets in very large transaction databases have been developed. The main focus of this paper is to analyze the implementations of the Frequent item set Mining algorithms such as SMine and Apriori Algorithms. General Terms-Data Mining, Frequent Item sets,...
متن کاملFrequent Item-set Mining without Ubiquitous Items
Frequent Item-set Mining (FIM), sometimes called Market Basket Analysis (MBA) or Association Rule Learning (ARL), are Machine Learning (ML) methods for creating rules from datasets of transactions of items. Most methods identify items likely to appear together in a transaction based on the support (i.e. a minimum number of relative co-occurrence of the items) for that hypothesis. Although this ...
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ژورنال
عنوان ژورنال: BMC Neuroscience
سال: 2012
ISSN: 1471-2202
DOI: 10.1186/1471-2202-13-s1-p126