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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 ...
Data preparation is the act of manipulating (or pre-processing) raw data (which may come from disparate data sources) into a form that can readily and accurately be analysed, e.g. for business purposes. [1]
Typically, users hand over the data transformation task to developers who have the necessary coding or technical skills to define the transformations and execute them on the data. [8] This process leaves the bulk of the work of defining the required transformations to the developer, which often in turn do not have the same domain knowledge as ...
Data scientists often work with unstructured data such as text or images and use machine learning algorithms to build predictive models and make data-driven decisions. In addition to statistical analysis , data science often involves tasks such as data preprocessing , feature engineering , and model selection.
The term data processing has mostly been subsumed by the more general term information technology (IT). [5] The older term "data processing" is suggestive of older technologies. For example, in 1996 the Data Processing Management Association (DPMA) changed its name to the Association of Information Technology Professionals. Nevertheless, the ...
A common example from computer programming is the processing performed on source code before the next step of compilation. In some computer languages (e.g., C and PL/I) there is a phase of translation known as preprocessing. It can also include macro processing, file inclusion and language extensions.
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
Data binning, also called data discrete binning or data bucketing, is a data pre-processing technique used to reduce the effects of minor observation errors. The original data values which fall into a given small interval, a bin , are replaced by a value representative of that interval, often a central value ( mean or median ).