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  2. 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 ...

  3. Preprocessor - Wikipedia

    en.wikipedia.org/wiki/Preprocessor

    The most common example of this is the C preprocessor, which takes lines beginning with '#' as directives. The C preprocessor does not expect its input to use the syntax of the C language. Some languages take a different approach and use built-in language features to achieve similar things. For example:

  4. 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 ...

  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. Comparison gallery of image scaling algorithms - Wikipedia

    en.wikipedia.org/wiki/Comparison_gallery_of...

    The resulting image is larger than the original, and preserves all the original detail, but has (possibly undesirable) jaggedness. The diagonal lines of the "W", for example, now show the "stairway" shape characteristic of nearest-neighbor interpolation. Other scaling methods below are better at preserving smooth contours in the image.

  7. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  8. C preprocessor - Wikipedia

    en.wikipedia.org/wiki/C_preprocessor

    The C preprocessor (CPP) is a text file processor that is used with C, C++ and other programming tools. The preprocessor provides for file inclusion (often header files ), macro expansion, conditional compilation , and line control.

  9. Data acquisition - Wikipedia

    en.wikipedia.org/wiki/Data_acquisition

    Data acquisition is the process of sampling signals that measure real-world physical conditions and converting the resulting samples into digital numeric values that can be manipulated by a computer. Data acquisition systems, abbreviated by the acronyms DAS, DAQ, or DAU, typically convert analog waveforms into digital values for processing.

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