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cons (e 1, l 1) = cons (e 2, l 2) if e 1 = e 2 and l 1 = l 2. Note that first (nil ()) and rest (nil ()) are not defined. These axioms are equivalent to those of the abstract stack data type. In type theory, the above definition is more simply regarded as an inductive type defined in terms of constructors: nil and cons.
"Using Hollerith's punchcard equipment, the Census Office was able to complete tabulating most of the 1890 census data in 2 to 3 years, compared with 7 to 8 years for the 1880 census. It is estimated that using Hollerith's system saved some $5 million in processing costs" [4] in 1890 dollars even though there were twice as many questions as in ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Data are usually organized into structures such as tables that provide additional context and meaning, and may themselves be used as data in larger structures. Data may be used as variables in a computational process. [1] [2] Data may represent abstract ideas or concrete measurements. [3]
In computer science, primitive data types are a set of basic data types from which all other data types are constructed. [1] Specifically it often refers to the limited set of data representations in use by a particular processor , which all compiled programs must use.
A data structure known as a hash table.. In computer science, a data structure is a data organization and storage format that is usually chosen for efficient access to data. [1] [2] [3] More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data, [4] i.e., it is an algebraic structure about data.
The data shown is a random sample of 10,000 points from a normal distribution with a mean of 0 and a standard deviation of 1. The data used to construct a histogram are generated via a function m i that counts the number of observations that fall into each of the disjoint categories (known as bins ).
Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5] It uses techniques and theories drawn from many fields within the context of mathematics , statistics, computer science , information science , and domain knowledge . [ 6 ]