Greedy algorithmA greedy algorithm is any algorithm that follows the problem-solving heuristic of making the locally optimal choice at each stage. In many problems, a greedy strategy does not produce an optimal solution, but a greedy heuristic can yield locally optimal solutions that approximate a globally optimal solution in a reasonable amount of time. For example, a greedy strategy for the travelling salesman problem (which is of high computational complexity) is the following heuristic: "At each step of the journey, visit the nearest unvisited city.
AlgorithmIn mathematics and computer science, an algorithm (ˈælɡərɪðəm) is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing calculations and data processing. More advanced algorithms can use conditionals to divert the code execution through various routes (referred to as automated decision-making) and deduce valid inferences (referred to as automated reasoning), achieving automation eventually.
Stability (learning theory)Stability, also known as algorithmic stability, is a notion in computational learning theory of how a machine learning algorithm output is changed with small perturbations to its inputs. A stable learning algorithm is one for which the prediction does not change much when the training data is modified slightly. For instance, consider a machine learning algorithm that is being trained to recognize handwritten letters of the alphabet, using 1000 examples of handwritten letters and their labels ("A" to "Z") as a training set.
Balanced budgetA balanced budget (particularly that of a government) is a budget in which revenues are equal to expenditures. Thus, neither a budget deficit nor a budget surplus exists (the accounts "balance"). More generally, it is a budget that has no budget deficit, but could possibly have a budget surplus. A cyclically balanced budget is a budget that is not necessarily balanced year-to-year but is balanced over the economic cycle, running a surplus in boom years and running a deficit in lean years, with these offsetting over time.
Government budget balanceThe government budget balance, also referred to as the general government balance, public budget balance, or public fiscal balance, is the difference between government revenues and spending. For a government that uses accrual accounting (rather than cash accounting) the budget balance is calculated using only spending on current operations, with expenditure on new capital assets excluded. A positive balance is called a government budget surplus, and a negative balance is a government budget deficit.
Yes–no questionIn linguistics, a yes–no question, also known as a binary question, a polar question, or a general question, is a question whose expected answer is one of two choices, one that provides an affirmative answer to the question versus one that provides a negative answer to the question. Typically, in English, the choices are either "yes" or "no". Yes–no questions present an exclusive disjunction, namely a pair of alternatives of which only one is a felicitous answer.
Data architectureData architecture consist of models, policies, rules, and standards that govern which data is collected and how it is stored, arranged, integrated, and put to use in data systems and in organizations. Data is usually one of several architecture domains that form the pillars of an enterprise architecture or solution architecture. A data architecture aims to set data standards for all its data systems as a vision or a model of the eventual interactions between those data systems.
Approximation algorithmIn computer science and operations research, approximation algorithms are efficient algorithms that find approximate solutions to optimization problems (in particular NP-hard problems) with provable guarantees on the distance of the returned solution to the optimal one. Approximation algorithms naturally arise in the field of theoretical computer science as a consequence of the widely believed P ≠ NP conjecture. Under this conjecture, a wide class of optimization problems cannot be solved exactly in polynomial time.
