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Data classification is the process of organizing data into categories based on attributes like file type, content, or metadata. The data is then assigned class labels that describe a set of attributes for the corresponding data sets. The goal is to provide meaningful class attributes to former less structured information.
The New Palgrave Dictionary of Economics, 2008, v. 8, Appendix IV, pp. 854–69, and for the online version by drilling to the primary, secondary, or tertiary JEL code of interest here and pressing the Search button below it for article-preview links. National Bureau of Economic Research Working Papers abstracts by year via links
A research design typically outlines the theories and models underlying a project; the research question(s) of a project; a strategy for gathering data and information; and a strategy for producing answers from the data. [1] A strong research design yields valid answers to research questions while weak designs yield unreliable, imprecise or ...
Data classification may refer to: Data classification (data management) Data classification (business intelligence) Classification (machine learning), classification of data using machine learning algorithms; Assigning a level of sensitivity to classified information; In computer science, the data type of a piece of data
The first step in doing a data classification is to cluster the data set used for category training, to create the wanted number of categories. An algorithm, called the classifier, is then used on the categories, creating a descriptive model for each. These models can then be used to categorize new items in the created classification system. [2]
In information science and ontology, a classification scheme is an arrangement of classes or groups of classes. The activity of developing the schemes bears similarity to taxonomy, but with perhaps a more theoretical bent, as a single classification scheme can be applied over a wide semantic spectrum while taxonomies tend to be devoted to a single topic.
For quantitative analysis, data is coded usually into measured and recorded as nominal or ordinal variables.. Questionnaire data can be pre-coded (process of assigning codes to expected answers on designed questionnaire), field-coded (process of assigning codes as soon as data is available, usually during fieldwork), post-coded (coding of open questions on completed questionnaires) or office ...
the 1991 version Archived 2017-09-21 at the Wayback Machine; the 1998 version; the current 2012 version. The ACM Computing Research Repository uses a classification scheme that is much coarser than the ACM subject classification, and does not cover all areas of CS, but is intended to better cover active areas of research. In addition, papers in ...