enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. SEMMA - Wikipedia

    en.wikipedia.org/wiki/SEMMA

    SEMMA is an acronym that stands for Sample, Explore, Modify, Model, and Assess. It is a list of sequential steps developed by SAS Institute , one of the largest producers of statistics and business intelligence software.

  3. Semantic analysis (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Semantic_analysis_(machine...

    In machine learning, semantic analysis of a text corpus is the task of building structures that approximate concepts from a large set of documents. It generally does not involve prior semantic understanding of the documents.

  4. Michael I. Jordan - Wikipedia

    en.wikipedia.org/wiki/Michael_I._Jordan

    Michael Irwin Jordan ForMemRS [6] (born February 25, 1956) is an American scientist, professor at the University of California, Berkeley, research scientist at the Inria Paris, and researcher in machine learning, statistics, and artificial intelligence.

  5. Cross-industry standard process for data mining - Wikipedia

    en.wikipedia.org/wiki/Cross-industry_standard...

    However, SAS Institute clearly states that SEMMA is not a data mining methodology, but rather a "logical organization of the functional toolset of SAS Enterprise Miner." A review and critique of data mining process models in 2009 called the CRISP-DM the "de facto standard for developing data mining and knowledge discovery projects."

  6. Precision and recall - Wikipedia

    en.wikipedia.org/wiki/Precision_and_recall

    In a classification task, the precision for a class is the number of true positives (i.e. the number of items correctly labelled as belonging to the positive class) divided by the total number of elements labelled as belonging to the positive class (i.e. the sum of true positives and false positives, which are items incorrectly labelled as belonging to the class).

  7. Computational learning theory - Wikipedia

    en.wikipedia.org/wiki/Computational_learning_theory

    Online machine learning, from the work of Nick Littlestone [citation needed]. While its primary goal is to understand learning abstractly, computational learning theory has led to the development of practical algorithms. For example, PAC theory inspired boosting, VC theory led to support vector machines, and Bayesian inference led to belief ...

  8. Garbage in, garbage out - Wikipedia

    en.wikipedia.org/wiki/Garbage_in,_garbage_out

    In computer science, garbage in, garbage out (GIGO) is the concept that flawed, biased or poor quality ("garbage") information or input produces a result or output of similar ("garbage") quality. The adage points to the need to improve data quality in, for example, programming.

  9. Semantics (computer science) - Wikipedia

    en.wikipedia.org/wiki/Semantics_(computer_science)

    In 1967, Robert W. Floyd published the paper Assigning meanings to programs; his chief aim was "a rigorous standard for proofs about computer programs, including proofs of correctness, equivalence, and termination". [2] [3] Floyd further wrote: [2] A semantic definition of a programming language, in our approach, is founded on a syntactic ...