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Arithmetic if is an unstructured control statement, and is not used in structured programming. In practice it has been observed that most arithmetic IF statements reference the following statement with one or two of the labels. This was the only conditional control statement in the original implementation of Fortran on the IBM 704 computer. On ...
Within an imperative programming language, a control flow statement is a statement that results in a choice being made as to which of two or more paths to follow. For non-strict functional languages, functions and language constructs exist to achieve the same result, but they are usually not termed control flow statements.
Conditional statements (if-then or if-then-else) in computer science, binary decisions about which piece of code to execute next. [3] Decision trees and binary decision diagrams, representations for sequences of binary decisions. [4] Binary choice, a statistical model for the outcome of a binary decision. [5]
Decision trees can also be seen as generative models of induction rules from empirical data. An optimal decision tree is then defined as a tree that accounts for most of the data, while minimizing the number of levels (or "questions"). [8] Several algorithms to generate such optimal trees have been devised, such as ID3/4/5, [9] CLS, ASSISTANT ...
Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
Decision tables are a concise visual representation for specifying which actions to perform depending on given conditions. Decision table is the term used for a Control table or State-transition table in the field of Business process modeling ; they are usually formatted as the transpose of the way they are formatted in Software engineering .
Markov decision process (MDP), also called a stochastic dynamic program or stochastic control problem, is a model for sequential decision making when outcomes are uncertain. [ 1 ] Originating from operations research in the 1950s, [ 2 ] [ 3 ] MDPs have since gained recognition in a variety of fields, including ecology , economics , healthcare ...
Until that time, the concept of an NP-complete problem did not even exist. The proof shows how every decision problem in the complexity class NP can be reduced to the SAT problem for CNF [a] formulas, sometimes called CNFSAT. A useful property of Cook's reduction is that it preserves the number of accepting answers.