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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. Data cleansing - Wikipedia

    en.wikipedia.org/wiki/Data_cleansing

    Data cleansing may also involve harmonization (or normalization) of data, which is the process of bringing together data of "varying file formats, naming conventions, and columns", [2] and transforming it into one cohesive data set; a simple example is the expansion of abbreviations ("st, rd, etc." to "street, road, etcetera").

  5. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Pre-processed data Check format details in the project's worksheet. Dialog/Instruction prompted 2020 [340] Michihiro et al. Natural Instructions v2 Large dataset that covers a wider range of reasoning abilities Each task consists of input/output, and a task definition. Additionally, each ask contains a task definition.

  6. Data transformation (computing) - Wikipedia

    en.wikipedia.org/wiki/Data_transformation...

    In computing, data transformation is the process of converting data from one format or structure into another format or structure. It is a fundamental aspect of most data integration [ 1 ] and data management tasks such as data wrangling , data warehousing , data integration and application integration.

  7. Preprocessor - Wikipedia

    en.wikipedia.org/wiki/Preprocessor

    Most preprocessors are specific to a particular data processing task (e.g., compiling the C language). A preprocessor may be promoted as being general purpose , meaning that it is not aimed at a specific usage or programming language, and is intended to be used for a wide variety of text processing tasks.

  8. Extract, transform, load - Wikipedia

    en.wikipedia.org/wiki/Extract,_transform,_load

    Data extraction involves extracting data from homogeneous or heterogeneous sources; data transformation processes data by data cleaning and transforming it into a proper storage format/structure for the purposes of querying and analysis; finally, data loading describes the insertion of data into the final target database such as an operational ...

  9. Data wrangling - Wikipedia

    en.wikipedia.org/wiki/Data_wrangling

    Data wrangling, sometimes referred to as data munging, is the process of transforming and mapping data from one "raw" data form into another format with the intent of making it more appropriate and valuable for a variety of downstream purposes such as analytics. The goal of data wrangling is to assure quality and useful data.