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Cluster Analysis
Cluster analysis or clustering is the data analyzing technique in which task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more Similarity measure, similar (in some specific sense defined by the analyst) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistics, statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Cluster analysis refers to a family of algorithms and tasks rather than one specific algorithm. It can be achieved by various algorithms that differ significantly in their understanding of what constitutes a cluster and how to efficiently find them. Popular notions of clusters include groups with small Distance function, distances between cluster members, dense areas of the data space, intervals or pa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Set
A data set (or dataset) is a collection of data. In the case of tabular data, a data set corresponds to one or more table (database), database tables, where every column (database), column of a table represents a particular Variable (computer science), variable, and each row (database), row corresponds to a given Record (computer science), record of the data set in question. The data set lists values for each of the variables, such as for example height and weight of an object, for each member of the data set. Data sets can also consist of a collection of documents or files. In the open data discipline, a dataset is a unit used to measure the amount of information released in a public open data repository. The European data.europa.eu portal aggregates more than a million data sets. Properties Several characteristics define a data set's structure and properties. These include the number and types of the attributes or variables, and various statistical measures applicable to the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multivariate Normal Distribution
In probability theory and statistics, the multivariate normal distribution, multivariate Gaussian distribution, or joint normal distribution is a generalization of the one-dimensional ( univariate) normal distribution to higher dimensions. One definition is that a random vector is said to be ''k''-variate normally distributed if every linear combination of its ''k'' components has a univariate normal distribution. Its importance derives mainly from the multivariate central limit theorem. The multivariate normal distribution is often used to describe, at least approximately, any set of (possibly) correlated real-valued random variables, each of which clusters around a mean value. Definitions Notation and parametrization The multivariate normal distribution of a ''k''-dimensional random vector \mathbf = (X_1,\ldots,X_k)^ can be written in the following notation: : \mathbf\ \sim\ \mathcal(\boldsymbol\mu,\, \boldsymbol\Sigma), or to make it explicitly known that \mathb ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
K-means Algorithm
''k''-means clustering is a method of vector quantization, originally from signal processing, that aims to partition ''n'' observations into ''k'' clusters in which each observation belongs to the cluster with the nearest mean (cluster centers or cluster centroid), serving as a prototype of the cluster. This results in a partitioning of the data space into Voronoi cells. ''k''-means clustering minimizes within-cluster variances ( squared Euclidean distances), but not regular Euclidean distances, which would be the more difficult Weber problem: the mean optimizes squared errors, whereas only the geometric median minimizes Euclidean distances. For instance, better Euclidean solutions can be found using ''k''-medians and ''k''-medoids. The problem is computationally difficult (NP-hard); however, efficient heuristic algorithms converge quickly to a local optimum. These are usually similar to the expectation–maximization algorithm for mixtures of Gaussian distributions via an i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hierarchical Clustering
In data mining and statistics, hierarchical clustering (also called hierarchical cluster analysis or HCA) is a method of cluster analysis that seeks to build a hierarchy of clusters. Strategies for hierarchical clustering generally fall into two categories: * Agglomerative: Agglomerative: Agglomerative clustering, often referred to as a "bottom-up" approach, begins with each data point as an individual cluster. At each step, the algorithm merges the two most similar clusters based on a chosen distance metric (e.g., Euclidean distance) and linkage criterion (e.g., single-linkage, complete-linkage). This process continues until all data points are combined into a single cluster or a stopping criterion is met. Agglomerative methods are more commonly used due to their simplicity and computational efficiency for small to medium-sized datasets . * Divisive: Divisive clustering, known as a "top-down" approach, starts with all data points in a single cluster and recursively splits the clu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Personality Psychology
Personality psychology is a branch of psychology that examines personality and its variation among individuals. It aims to show how people are individually different due to psychological forces. Its areas of focus include: * Describing what personality is * Documenting how personalities develop * Explaining the mental processes of personality and how they affect functioning * Providing a framework for understanding Individual, individuals "Personality" is a dynamic and organized set of characteristics possessed by an individual that uniquely influences their environment, cognition, emotions, motivations, and Behavioural sciences, behaviors in various situations. The word ''personality'' originates from the Latin ''persona'', which means "mask". Personality also pertains to the pattern of thoughts, feelings, Adjustment (psychology), social adjustments, and behaviors persistently exhibited over time that strongly influences one's expectations, Self-concept, self-perceptions, Valu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Raymond Cattell
Raymond Bernard Cattell (20 March 1905 – 2 February 1998) was a British-American psychologist, known for his psychometric research into intrapersonal psychological structure.Gillis, J. (2014). ''Psychology's Secret Genius: The Lives and Works of Raymond B. Cattell''. Amazon Kindle Edition. His work also explored the basic dimensions of personality and temperament, the range of cognitive abilities, the dynamic dimensions of motivation and emotion, the clinical dimensions of abnormal personality, patterns of group syntality and social behavior, applications of personality research to psychotherapy and learning theory,Cattell, R. B. (1987). ''Psychotherapy by Structured Learning Theory''. New York: Springer. predictors of creativity and achievement, and many multivariate research methodsCattell, R. B. (1966). (Ed.), ''Handbook of Multivariate Experimental Psychology''. Chicago, IL: Rand McNally. including the refinement of factor analytic methods for exploring and measuring these ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Robert Tryon
Robert Choate Tryon (September 4, 1901 – September 27, 1967) was an American behavioral psychologist, who pioneered the study of hereditary trait inheritance and learning in animals. His series of experiments with laboratory rats showed that animals can be selectively bred for greater aptitude at certain intelligence tests, but that this selective breeding does not increase the general intelligence of the animals. Life Tryon was born in Butte, Montana on September 4, 1901. He spent most of his life at the University of California, Berkeley. He received his AB degree from the undergraduate school in 1924, and as a graduate student he earned his Ph.D. in 1928 with a thesis titled ''Individual differences at successive stages of learning''. After graduating from the school he spent two years as a National Research Council fellow. In 1931, he became a faculty member of the college's Department of Psychology, of which he was a member for 31 years. During the War, he served i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Joseph Zubin
Joseph Zubin (9 October 1900 18 December 1990) was a Lithuanian-born American educational psychologist and an authority on schizophrenia who is commemorated by the Joseph Zubin Awards.''New York Times'' Dec 12, 1990 Dr. Joseph Zubin, 90, Research Psychologist He was the founder of the Biometrics Research Department of New York State Psychiatric Institute. Life Zubin was born October 9, 1900, in Raseiniai, , but move ...[...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Community Structure
In the study of complex networks, a network is said to have community structure if the nodes of the network can be easily grouped into (potentially overlapping) sets of nodes such that each set of nodes is densely connected internally. In the particular case of ''non-overlapping'' community finding, this implies that the network divides naturally into groups of nodes with dense connections internally and sparser connections between groups. But ''overlapping'' communities are also allowed. The more general definition is based on the principle that pairs of nodes are more likely to be connected if they are both members of the same community(ies), and less likely to be connected if they do not share communities. A related but different problem is community search, where the goal is to find a community that a certain vertex belongs to. Properties In the study of networks, such as computer and information networks, social networks and biological networks, a number of different chara ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Numerical Taxonomy
Numerical taxonomy is a classification system in biological systematics which deals with the grouping by numerical methods of taxonomic units based on their character states. It aims to create a taxonomy using numeric algorithms like cluster analysis rather than using subjective evaluation of their properties. The concept was first developed by Robert R. Sokal and Peter H. A. Sneath in 1963 and later elaborated by the same authors.Sneath and Sokal: ''Numerical Taxonomy'', San Francisco: W.H. Freeman, 1974 by Tejanshu Ravesh They divided the field into phenetics in which classifications are formed based on the patterns of overall similarities and cladistics in which classifications are based on the branching patterns of the estimated evolutionary history of the taxa.{{cn span, In recent years many authors treat numerical taxonomy and phenetics as synonyms despite the distinctions made by those authors., date=May 2017 Although intended as an objective method, in practice the ch ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
