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1 algoritmo de clustering
(n.) = clustering algorithmEx. Traditional clustering algorithms either favour clusters with spherical shapes and similar sizes, or are very fragile in the presence of outliers.* * *(n.) = clustering algorithmEx: Traditional clustering algorithms either favour clusters with spherical shapes and similar sizes, or are very fragile in the presence of outliers.
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2 valor atípico
m.outlier.* * *(n.) = outlierEx. Traditional clustering algorithms either favour clusters with spherical shapes and similar sizes, or are very fragile in the presence of outliers.* * *(n.) = outlierEx: Traditional clustering algorithms either favour clusters with spherical shapes and similar sizes, or are very fragile in the presence of outliers.
См. также в других словарях:
Clustering high-dimensional data — is the cluster analysis of data with anywhere from a few dozen to many thousands of dimensions. Such high dimensional data spaces are often encountered in areas such as medicine, where DNA microarray technology can produce a large number of… … Wikipedia
Consensus clustering — Clustering is the assignment of objects into groups (called clusters) so that objects from the same cluster are more similar to each other than objects from different clusters. Often similarity is assessed according to a distance measure.… … Wikipedia
k-means clustering — In statistics and data mining, k means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. This results into a partitioning of… … Wikipedia
Data stream clustering — In computer science, data stream clustering is defined as the clustering of data that arrive continuously such as telephone records, multimedia data, financial transactions etc. Data stream clustering is usually studied under the data stream… … Wikipedia
Fuzzy clustering — is a class of algorithm in computer science. Explanation of clustering Data clustering is the process of dividing data elements into classes or clusters so that items in the same class are as similar as possible, and items in different classes… … Wikipedia
CURE data clustering algorithm — CURE (Clustering Using REpresentatives) is an efficient data clustering algorithm for large databases that is more robust to outliers and identifies clusters having non spherical shapes and wide variances in size. Contents 1 Drawbacks of… … Wikipedia
Constrained clustering — In computer science, constrained clustering is a class of semi supervised learning algorithms. Typically, constrained clustering incorporates either a set of must link constraints, cannot link constraints, or both, with a Data clustering… … Wikipedia
Complete-linkage clustering — In cluster analysis, complete linkage or farthest neighbour is a method of calculating distances between clusters in agglomerative hierarchical clustering. In complete linkage,[1] the distance between two clusters is computed as the maximum… … Wikipedia
Correlation clustering — In machine learning, correlation clustering or cluster editing operates in a scenario where the relationship between the objects are known instead of the actual representation of the objects. For example, given a signed graph G = (V,E) where the… … Wikipedia
Sequence clustering — In bioinformatics, sequence clustering algorithms attempt to group sequences that are somehow related. The sequences can be either of genomic, transcriptomic (ESTs) or protein origin.For proteins, homologous sequences are typically grouped into… … Wikipedia
Single-linkage clustering — In cluster analysis, single linkage, nearest neighbour or shortest distance is a method of calculating distances between clusters in hierarchical clustering. In single linkage, the distance between two clusters is computed as the distance between … Wikipedia
