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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 ).
Data binning: a data pre-processing technique. Binning (metagenomics): the process of classifying reads into different groups or taxonomies. Product binning: in semiconductor device fabrication, the process of categorizing finished products. Pixel binning: the process of combining charge from adjacent pixels in a CCD image sensor during readout.
Bahasa Indonesia: Modul ini adalah Panduan untuk pengajar program "Reading Wikipedia in the Classroom" yang telah dilokalkan ke bahasa Indonesia menjadi "Menggunakan Wikipedia dalam Pembelajaran" (Modul 1). "Reading Wikipedia in the Classroom" adalah program pengembangan profesional untuk guru sekolah menengah yang diinisiasi oleh tim ...
In computer programming, data-binding is a general technique that binds data sources from the provider and consumer together and synchronizes them. This is usually done with two data/information sources with different languages, as in XML data binding and UI data binding .
The Indonesian Wikipedia (Indonesian: Wikipedia bahasa Indonesia, WBI for short) is the Indonesian language edition of Wikipedia. It is the fifth-fastest-growing Asian-language Wikipedia after the Japanese, Chinese, Korean, and Turkish language Wikipedias. It ranks 25th in terms of depth among Wikipedias.
Wikipedia and its sister projects—e.g. Wikimedia Commons, WikiSource—supported by the Wikimedia Foundation are hosted by servers (see Wikimedia servers on Meta-Wiki) at a data center in the state of Virginia, with an emergency backup data center in the state of Texas; caching servers are located in the Netherlands and Singapore.
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The difference between data analysis and data mining is that data analysis is used to test models and hypotheses on the dataset, e.g., analyzing the effectiveness of a marketing campaign, regardless of the amount of data. In contrast, data mining uses machine learning and statistical models to uncover clandestine or hidden patterns in a large ...