Results 11 to 20 of about 2,690 (229)
arules - A Computational Environment for Mining Association Rules and Frequent Item Sets [PDF]
Mining frequent itemsets and association rules is a popular and well researched approach for discovering interesting relationships between variables in large databases.
Michael Hahsler +2 more
doaj +2 more sources
Frequent regular itemset mining [PDF]
Concise representations of frequent itemsets sacrifice readability and direct interpretability by a data analyst of the concise patterns extracted. In this paper, we introduce an extension of itemsets, called regular, with an immediate semantics and interpretability, and a conciseness comparable to closed itemsets. Regular itemsets allow for specifying
RUGGIERI, SALVATORE, Salvatore Ruggieri
openaire +4 more sources
Mining All Non-derivable Frequent Itemsets [PDF]
3 ...
Toon Calders, Bart Goethals
openaire +7 more sources
Theoretical Properties of Closed Frequent Itemsets in Frequent Pattern Mining
Closed frequent itemsets (CFIs) play a crucial role in frequent pattern mining by providing a compact and complete representation of all frequent itemsets (FIs).
Huina Zhang +4 more
doaj +2 more sources
Behavior Decoding Delineates Seizure Microfeatures and Associated Sudden Death Risks in Mouse Models of Epilepsy. [PDF]
Objective Behavior and motor manifestations are distinctive yet often overlooked features of epileptic seizures. Seizures can result in transient disruptions in motor control, often organized into specific behavioral sequences that can inform seizure types, onset zones, and outcomes.
Shen Y +8 more
europepmc +2 more sources
One of the most challenging tasks in association rule mining is that when a new incremental database is added to an original database, some existing frequent itemsets may become infrequent itemsets and vice versa.
Wannasiri Thurachon, Worapoj Kreesuradej
doaj +1 more source
MAXLEN-FI: AN ALGORITHM FOR MINING MAXIMUM- LENGTH FREQUENT ITEMSETS FAST
Association rule mining, one of the most important and well-researched techniques of data mining. Mining frequent itemsets are one of the most fundamental and most time-consuming problems in association rule mining.
Phan Thành Huấn, Lê Hoài Bắc
doaj +1 more source
Efficient Mining of Frequent Itemsets Using Only One Dynamic Prefix Tree
Frequent itemset mining is a fundamental problem in data mining area because frequent itemsets have been extensively used in reasoning, classifying, clustering, and so on.
Jun-Feng Qu +5 more
doaj +1 more source
Memory-efficient frequent-itemset mining
Efficient discovery of frequent itemsets in large datasets is a key component of many data mining tasks. In-core algorithms---which operate entirely in main memory and avoid expensive disk accesses---and in particular the prefix tree-based algorithm FP-growth are generally among the most efficient of the available algorithms.
Benjamin Schlegel +2 more
openaire +3 more sources
Weighted Association Rule Mining using Weighted Support and Significance Framework [PDF]
We address the issues of discovering significant binary relationships in transaction datasets in a weighted setting. Traditional model of association rule mining is adapted to handle weighted association rule mining problems where each item is allowed to
Feng Tao +5 more
core +1 more source

