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In computer science, the count-distinct problem [1] (also known in applied mathematics as the cardinality estimation problem) is the problem of finding the number of distinct elements in a data stream with repeated elements. This is a well-known problem with numerous applications.
Mandatory Constraints: Certain columns cannot be empty. Unique Constraints: A field, or a combination of fields, must be unique across a dataset. For example, no two persons can have the same social security number. Set-Membership constraints: The values for a column come from a set of discrete values or codes. For example, a person's sex may ...
In this method, certain values of the attributes are replaced by an asterisk "*". All or some values of a column may be replaced by "*". In the anonymized table below, we have replaced all the values in the Name attribute and all the values in the Religion attribute with a "*". Generalization. In this method, individual values of attributes are ...
In a database, a table is a collection of related data organized in table format; consisting of columns and rows.. In relational databases, and flat file databases, a table is a set of data elements (values) using a model of vertical columns (identifiable by name) and horizontal rows, the cell being the unit where a row and column intersect. [1]
A candidate key comprises a single column or a set of columns in a single database table. No two distinct rows or data records in a database table can have the same data value (or combination of data values) in those candidate key columns since NULL values are not used.
Each of the parts is then set aside at turn as a test set, a clustering model computed on the other v − 1 training sets, and the value of the objective function (for example, the sum of the squared distances to the centroids for k-means) calculated for the test set. These v values are calculated and averaged for each alternative number of ...
In computer science, a set is an abstract data type that can store unique values, without any particular order. It is a computer implementation of the mathematical concept of a finite set . Unlike most other collection types, rather than retrieving a specific element from a set, one typically tests a value for membership in a set.
The iterative proportional fitting procedure (IPF or IPFP, also known as biproportional fitting or biproportion in statistics or economics (input-output analysis, etc.), RAS algorithm [1] in economics, raking in survey statistics, and matrix scaling in computer science) is the operation of finding the fitted matrix which is the closest to an initial matrix but with the row and column totals of ...