Search results
Results From The WOW.Com Content Network
In computer science, an order statistic tree is a variant of the binary search tree (or more generally, a B-tree [1]) that supports two additional operations beyond insertion, lookup and deletion: Select( i ) – find the i -th smallest element stored in the tree
Given a binary product-machines n-by-m matrix, the algorithm proceeds [2] by the following steps: . Compute the similarity coefficient = / (+) for all with being the number of products that need to be processed on both machine i and machine j, u comprises the number of components which visit machine j but not k and vice versa.
These arise when individuals rank objects in order of preference. The data are then ordered lists of objects, arising in voting, education, marketing and other areas. Model-based clustering methods for rank data include mixtures of Plackett-Luce models and mixtures of Benter models, [29] [30] and mixtures of Mallows models. [31]
CURE (no. of points,k) Input : A set of points S Output : k clusters For every cluster u (each input point), in u.mean and u.rep store the mean of the points in the cluster and a set of c representative points of the cluster (initially c = 1 since each cluster has one data point).
Learning to rank [1] or machine-learned ranking (MLR) is the application of machine learning, typically supervised, semi-supervised or reinforcement learning, in the construction of ranking models for information retrieval systems. [2]
List ranking can equivalently be viewed as performing a prefix sum operation on the given list, in which the values to be summed are all equal to one. The list ranking problem can be used to solve many problems on trees via an Euler tour technique, in which one forms a linked list that includes two copies of each edge of the tree, one in each direction, places the nodes of this list into an ...
Given any list as an input: Count the number of elements. Given a list of numbers: Find the k largest or smallest elements, k given in advance. Find the sum, mean, variance and standard deviation of the elements of the list. See also Algorithms for calculating variance. Given a list of symbols from an alphabet of k symbols, given in advance.
List comprehension is a syntactic construct available in some programming languages for creating a list based on existing lists. It follows the form of the mathematical set-builder notation (set comprehension) as distinct from the use of map and filter functions.