clustering analysis
11Gene chip analysis — Introduction Microarray is a powerful tool for genome analysis. It gives the global view of the genome analysis in a single experiment. Data analysis in the Microarray is a vital part as this part influences the final result. Each microarray… …
12Cluster analysis (in marketing) — Cluster analysis is a class of statistical techniques that can be applied to data that exhibit “natural” groupings. Cluster analysis sorts through the raw data and groups them into clusters. A cluster is a group of relatively homogeneous cases or …
13Principal component analysis — PCA of a multivariate Gaussian distribution centered at (1,3) with a standard deviation of 3 in roughly the (0.878, 0.478) direction and of 1 in the orthogonal direction. The vectors shown are the eigenvectors of the covariance matrix scaled by… …
14Principal components analysis — Principal component analysis (PCA) is a vector space transform often used to reduce multidimensional data sets to lower dimensions for analysis. Depending on the field of application, it is also named the discrete Karhunen Loève transform (KLT),… …
15Conceptual clustering — is a machine learning paradigm for unsupervised classification developed mainly during the 1980s. It is distinguished from ordinary data clustering by generating a concept description for each generated class. Most conceptual clustering methods… …
16cluster analysis — A form of multivariate analysis , of which the purpose is to divide a set of objects (such as variables or individuals), characterized by a number of attributes, into a set of clusters or classes, in such a way that the objects in a class are… …
17Complete-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… …
18Latent semantic analysis — (LSA) is a technique in natural language processing, in particular in vectorial semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms. LSA was …
19Power graph analysis — In computational biology, power graph analysis is a method for the analysis andrepresentation of complex networks. Power graph analysis is the computation, analysis and visual representation of a power graph from a graphs (networks).Power graph… …
20Correlation 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… …
