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Anonymous asked in 電腦及互聯網軟體 · 1 decade ago

excel 問題


what mean is Data Mining

thank you

1 Answer

  • joe
    Lv 7
    1 decade ago
    Favorite Answer


    Data mining is the process of extracting patterns from data. As more data are gathered, with the amount of data doubling every three years,[1] data mining is becoming an increasingly important tool to transform these data into information. It is commonly used in a wide range of profiling practices, such as marketing, surveillance, fraud detection and scientific discovery.

    While data mining can be used to uncover patterns in data samples, it is important to be aware that the use of non-representative samples of data may produce results that are not indicative of the domain. Similarly, data mining will not find patterns that may be present in the domain, if those patterns are not present in the sample being "mined". There is a tendency for insufficiently knowledgeable "consumers" of the results to attribute "magical abilities" to data mining, treating the technique as a sort of all-seeing crystal ball. Further, the discovery of a particular pattern in a particular set of data does not necessarily mean that pattern is representative of the whole population from which that data was drawn. Hence, an important part of the process is the verification and validation of patterns on other samples of data.

    The term data mining has also been used in a related but negative sense, to mean the deliberate searching for apparent but not necessarily representative patterns in large numbers of data. .


    1 Background

    1.1 Research and evolution 2 Process

    2.1 Pre-processing

    2.2 Data mining

    2.3 Results validation 3 Notable uses

    3.1 Games

    3.2 Business

    3.3 Science and engineering

    3.4 Spatial Data mining

    3.4.1 Challenges 3.5 Surveillance

    3.5.1 Pattern mining

    3.5.2 Subject-based data mining 4 Privacy concerns and ethics

    5 Marketplace surveys

    6 Groups and Associations

    7 See also

    7.1 Applications

    7.2 Methods

    7.3 Miscellaneous

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