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  2. Data preparation - Wikipedia

    en.wikipedia.org/wiki/Data_preparation

    Given the variety of data sources (e.g. databases, business applications) that provide data and formats that data can arrive in, data preparation can be quite involved and complex. There are many tools and technologies [5] that are used for data preparation. The cost of cleaning the data should always be balanced against the value of the ...

  3. Data preprocessing - Wikipedia

    en.wikipedia.org/wiki/Data_Preprocessing

    Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...

  4. Preprocessor - Wikipedia

    en.wikipedia.org/wiki/Preprocessor

    The output is said to be a preprocessed form of the input data, which is often used by some subsequent programs like compilers. The amount and kind of processing done depends on the nature of the preprocessor; some preprocessors are only capable of performing relatively simple textual substitutions and macro expansions, while others have the ...

  5. Preprocessing - Wikipedia

    en.wikipedia.org/wiki/Preprocessing

    Preprocessing can refer to the following topics in computer science: Preprocessor , a program that processes its input data to produce output that is used as input to another program like a compiler Data pre-processing , used in machine learning and data mining to make input data easier to work with

  6. Data wrangling - Wikipedia

    en.wikipedia.org/wiki/Data_wrangling

    An example of data mining that is closely related to data wrangling is ignoring data from a set that is not connected to the goal: say there is a data set related to the state of Texas and the goal is to get statistics on the residents of Houston, the data in the set related to the residents of Dallas is not useful to the overall set and can be ...

  7. Feature (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Feature_(machine_learning)

    In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a data set. [1] Choosing informative, discriminating, and independent features is crucial to produce effective algorithms for pattern recognition, classification, and regression tasks.

  8. Princess Kate and William to Launch Mental Health Program in 2025

    www.aol.com/lifestyle/princess-kate-william...

    The Waleses are staying true to their pledge to provide support for rural and farming communities in Norfolk.

  9. Stiction - Wikipedia

    en.wikipedia.org/wiki/Stiction

    Stiction (a portmanteau of the words static and friction) [1] is the force that needs to be overcome to enable relative motion of stationary objects in contact. [2] Any solid objects pressing against each other (but not sliding) will require some threshold of force parallel to the surface of contact in order to overcome static adhesion. [3]