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Dasgupta and Maskin proposed the Borda count as a Copeland tie-break: this is known as the Dasgupta-Maskin method. [11] It had previously been used in figure-skating under the name of the 'OBO' (=one-by-one) rule. [5] The alternatives can be illustrated in the 'Able-Baker' example above, in which Able and Baker are joint Copeland winners.
The Borda count has been proposed as a rank aggregation method in information retrieval, in which documents are ranked according to multiple criteria and the resulting rankings are then combined into a composite ranking. In this method, the ranking criteria are treated as voters, and the aggregate ranking is the result of applying the Borda ...
Instant-runoff does not comply with the Condorcet criterion, i.e. it is possible for it to elect a candidate that could lose in a head to head contest against another candidate in the election. For example, the following vote count of preferences with three candidates {A, B, C}: A > B > C: 35; C > B > A: 34; B > C > A: 31
For data in which the maximum key size is significantly smaller than the number of data items, counting sort may be parallelized by splitting the input into subarrays of approximately equal size, processing each subarray in parallel to generate a separate count array for each subarray, and then merging the count arrays.
Such items do not count towards criteria 1(a), 3(a)(ii), or 3(b)(i). The topic should contain an introductory paragraph that summarizes the topic for any reader who might want to find more about it. This paragraph should be a short version of the introduction of the lead article. See this for a specific example.
The term has been used to identify the different criteria that are used to evaluate a phylogenetic tree. For example, in order to determine the best topology between two phylogenetic trees using the maximum likelihood optimality criterion, one would calculate the maximum likelihood score of each tree and choose the one that had the better score.
The statistical treatment of count data is distinct from that of binary data, in which the observations can take only two values, usually represented by 0 and 1, and from ordinal data, which may also consist of integers but where the individual values fall on an arbitrary scale and only the relative ranking is important. [example needed]
In decision theory, the weighted sum model (WSM), [1] [2] also called weighted linear combination (WLC) [3] or simple additive weighting (SAW), [4] is the best known and simplest multi-criteria decision analysis (MCDA) / multi-criteria decision making method for evaluating a number of alternatives in terms of a number of decision criteria.