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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.
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 .
Data binning From an alternative name : This is a redirect from a title that is another name or identity such as an alter ego, a nickname, or a synonym of the target, or of a name associated with the target.
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Before data mining algorithms can be used, a target data set must be assembled. As data mining can only uncover patterns actually present in the data, the target data set must be large enough to contain these patterns while remaining concise enough to be mined within an acceptable time limit. A common source for data is a data mart or data ...
Wikidata is a collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation. [2] It is a common source of open data that Wikimedia projects such as Wikipedia, [3] [4] and anyone else, is able to use under the CC0 public domain license.
Gradient-based one-side sampling (GOSS) is a method that leverages the fact that there is no native weight for data instance in GBDT. Since data instances with different gradients play different roles in the computation of information gain, the instances with larger gradients will contribute more to the information gain.