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Apriori [1] is an algorithm for frequent item set mining and association rule learning over relational databases. It proceeds by identifying the frequent individual items in the database and extending them to larger and larger item sets as long as those item sets appear sufficiently often in the database.
For example a 10^4 frequent 1-itemset will generate a 10^7 candidate 2-itemset. The algorithm also needs to frequently scan the database, to be specific n+1 scans where n is the length of the longest pattern. Apriori is slower than the Eclat algorithm. However, Apriori performs well compared to Eclat when the dataset is large.
Frequent pattern discovery (or FP discovery, FP mining, or Frequent itemset mining) is part of knowledge discovery in databases, Massive Online Analysis, and data mining; it describes the task of finding the most frequent and relevant patterns in large datasets. [1] [2] The concept was first introduced for mining transaction databases. [3]
There are two important metrics for performing the association rules mining technique: support and confidence. Also, a priori algorithm is used to reduce the search space for the problem. [1] The support metric in the association rule learning algorithm is defined as the frequency of the antecedent or consequent appearing together in a data set ...
A survey and taxonomy of the key algorithms for item set mining is presented by Han et al. (2007). [5] The two common techniques that are applied to sequence databases for frequent itemset mining are the influential apriori algorithm and the more-recent FP-growth technique.
Classification algorithms (3 C, 85 P) Cluster analysis algorithms (42 P) Pages in category "Data mining algorithms" ... Apriori algorithm; G. GSP algorithm; I ...
Well, the apriori algorithm might be outdated but a) this page is about that algorithm! and b) not necessary to state, but it is the first significant algorithm, and the basic idea is used again and again in several succeeding algorithms so it is important to understand it.Exa 18:33, 16 May 2007 (UTC)
An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems.. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations.