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  2. Apriori algorithm - Wikipedia

    en.wikipedia.org/wiki/Apriori_algorithm

    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.

  3. Association rule learning - Wikipedia

    en.wikipedia.org/wiki/Association_rule_learning

    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.

  4. Frequent pattern discovery - Wikipedia

    en.wikipedia.org/wiki/Frequent_pattern_discovery

    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]

  5. Affinity analysis - Wikipedia

    en.wikipedia.org/wiki/Affinity_analysis

    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 ...

  6. Lift (data mining) - Wikipedia

    en.wikipedia.org/wiki/Lift_(data_mining)

    In data mining and association rule learning, lift is a measure of the performance of a targeting model (association rule) at predicting or classifying cases as having an enhanced response (with respect to the population as a whole), measured against a random choice targeting model.

  7. Sequential pattern mining - Wikipedia

    en.wikipedia.org/wiki/Sequential_Pattern_Mining

    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.

  8. Talk:Apriori algorithm - Wikipedia

    en.wikipedia.org/wiki/Talk:Apriori_algorithm

    Then we say that (all?) other algorithms are for finding association rules on non-transactional data, which is obviously not the case. Also, is Apriori really for "learning association rules"? To me it looks like the output of the algorithm is a set of frequencies of data per transaction, not a set of association rules.

  9. List of algorithms - Wikipedia

    en.wikipedia.org/wiki/List_of_algorithms

    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.