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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. 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 ...

  4. Preprocessor - Wikipedia

    en.wikipedia.org/wiki/Preprocessor

    For some programming languages, the rules are written in the same language as the program (compile-time reflection). This is the case with Lisp and OCaml . Some other languages rely on a fully external language to define the transformations, such as the XSLT preprocessor for XML , or its statically typed counterpart CDuce.

  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. Import and export of data - Wikipedia

    en.wikipedia.org/wiki/Import_and_export_of_data

    The import and export of data is the automated or semi-automated input and output of data sets between different software applications.It involves "translating" from the format used in one application into that used by another, where such translation is accomplished automatically via machine processes, such as transcoding, data transformation, and others.

  7. 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 ...

  8. General-purpose macro processor - Wikipedia

    en.wikipedia.org/wiki/General-purpose_macro...

    Text Assembler is a general-purpose text/macro processor based on the JavaScript programming language. Beyond simple macro replacement, it allows evaluating arbitrary JavaScript expressions and executing JavaScript code. It can also load JSON data models for more complex data-driven text processing tasks. [9] PP 2016

  9. KNIME - Wikipedia

    en.wikipedia.org/wiki/KNIME

    KNIME (/ n aɪ m / ⓘ), the Konstanz Information Miner, [2] is a free and open-source data analytics, reporting and integration platform.KNIME integrates various components for machine learning and data mining through its modular data pipelining "Building Blocks of Analytics" concept.