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This was one of the first uses of map-based spatial analysis. Spatial analysis is any of the formal techniques which studies entities using their topological, geometric, or geographic properties. Spatial analysis includes a variety of techniques using different analytic approaches, especially spatial statistics.
Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science ...
A geographic information system (GIS) consists of integrated computer hardware and software that store, manage, analyze, edit, output, and visualize geographic data. [1][2] Much of this often happens within a spatial database; however, this is not essential to meet the definition of a GIS. [1] In a broader sense, one may consider such a system ...
Suitability analysis is the process and procedures used to establish the suitability of a system – that is, the ability of a system to meet the needs of a stakeholder or other user. Before GIS (a computerized method that helps to determine suitability analysis) was widely used in the mid to late 20th century, city planners communicated their ...
Machine learningand data mining. A self-organizing map (SOM) or self-organizing feature map (SOFM) is an unsupervised machine learning technique used to produce a low-dimensional (typically two-dimensional) representation of a higher-dimensional data set while preserving the topological structure of the data.
e. In Bayesian statistics, a maximum a posteriori probability (MAP) estimate is an estimate of an unknown quantity, that equals the mode of the posterior distribution. The MAP can be used to obtain a point estimate of an unobserved quantity on the basis of empirical data. It is closely related to the method of maximum likelihood (ML) estimation ...
Geographic analytics is an analytical approach to strategic management and data analytics to make geographic decisions efficiently. Examples of such decisions are choosing the location for a warehouse or planning the regions for a marketing campaign. Data, information and framing conditions are visualized on maps to derive recommendations for ...
Metric multidimensional scaling (mMDS) It is a superset of classical MDS that generalizes the optimization procedure to a variety of loss functions and input matrices of known distances with weights and so on. A useful loss function in this context is called stress, which is often minimized using a procedure called stress majorization.
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