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Multi-attribute global inference of quality (MAGIQ) is a multi-criteria decision analysis technique. MAGIQ is based on a hierarchical decomposition of comparison attributes and rating assignment using rank order centroids.
The MAGIQ technique is used to assign a single, overall measure of quality to each member of a set of systems where each system has an arbitrary number of comparison attributes. The MAGIQ technique has features similar to the analytic hierarchy process and the simple multi-attribute rating technique exploiting ranks (SMARTER) technique. The MAGIQ technique was first published by James D. McCaffrey. The MAGIQ process begins with an evaluator determining which system attributes are to be used as the basis for system comparison. These attributes are ranked by importance to the particular problem domain, and the ranks are converted to ratings using rank order centroids. Each system under analysis is ranked against each comparison attribute and the ranks are transformed into rank order centroids. The final overall quality metric for each system is the weighted (by comparison attribute importance) sum of each attribute rating. The references provide specific examples of the process. There is little direct research on the theoretical soundness and effectiveness of the MAGIQ technique as a whole, however the use of hierarchical decomposition and the use of rank order centroids in multi-criteria decision analyses have been studied, with generally positive results. Anecdotal evidence suggests that the MAGIQ technique is both practical and useful.
In mathematics, functional decomposition is the process of resolving a functional relationship into its constituent parts in such a way that the original function can be reconstructed from those parts by function composition.
Unsupervised learning (UL) is a type of algorithm that learns patterns from untagged data. The hope is that, through mimicry, the machine is forced to build a compact internal representation of its world and then generate imaginative content. In contrast to supervised learning (SL) where data is tagged by a human, e.g. as "car" or "fish" etc, UL exhibits self-organization that captures patterns as neuronal predilections or probability densities. The other levels in the supervision spectrum are reinforcement learning where the machine is given only a numerical performance score as its guidance, and semi-supervised learning where a smaller portion of the data is tagged. Two broad methods in UL are Neural Networks and Probabilistic Methods.
In the social sciences, scaling is the process of measuring or ordering entities with respect to quantitative attributes or traits. For example, a scaling technique might involve estimating individuals' levels of extraversion, or the perceived quality of products. Certain methods of scaling permit estimation of magnitudes on a continuum, while other methods provide only for relative ordering of the entities.
Conjoint analysis is a survey-based statistical technique used in market research that helps determine how people value different attributes that make up an individual product or service.
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning.
Multiple-criteria decision-making (MCDM) or multiple-criteria decision analysis (MCDA) is a sub-discipline of operations research that explicitly evaluates multiple conflicting criteria in decision making. Conflicting criteria are typical in evaluating options: cost or price is usually one of the main criteria, and some measure of quality is typically another criterion, easily in conflict with the cost. In purchasing a car, cost, comfort, safety, and fuel economy may be some of the main criteria we consider – it is unusual that the cheapest car is the most comfortable and the safest one. In portfolio management, managers are interested in getting high returns while simultaneously reducing risks; however, the stocks that have the potential of bringing high returns typically carry high risk of losing money. In a service industry, customer satisfaction and the cost of providing service are fundamental conflicting criteria.
The analytic hierarchy process (AHP), also analytical hierarchy process, is a structured technique for organizing and analyzing complex decisions, based on mathematics and psychology. It was developed by Thomas L. Saaty in the 1970s; Saaty partnered with Ernest Forman to develop Expert Choice software in 1983, and AHP has been extensively studied and refined since then. It represents an accurate approach to quantifying the weights of decision criteria. Individual experts’ experiences are utilized to estimate the relative magnitudes of factors through pair-wise comparisons. Each of the respondents compares the relative importance each pair of items using a specially designed questionnaire.
Address geocoding, or simply geocoding, is the process of taking a text-based description of a location, such as an address or the name of a place, and returning geographic coordinates, frequently latitude/longitude pair, to identify a location on the Earth's surface. Reverse geocoding, on the other hand, converts geographic coordinates to a description of a location, usually the name of a place or an addressable location. Geocoding relies on a computer representation of address points, the street / road network, together with postal and administrative boundaries.
Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.
Pairwise comparison generally is any process of comparing entities in pairs to judge which of each entity is preferred, or has a greater amount of some quantitative property, or whether or not the two entities are identical. The method of pairwise comparison is used in the scientific study of preferences, attitudes, voting systems, social choice, public choice, requirements engineering and multiagent AI systems. In psychology literature, it is often referred to as paired comparison.
James D. McCaffrey is a software researcher and author known for his contributions to the fields of mathematical combinatorics and software test automation. McCaffrey holds a PhD in cognitive psychology and computational statistics from the University of Southern California, and degrees in psychology and applied mathematics from the University of California, Irvine and California State University, Fullerton.
The analytic network process (ANP) is a more general form of the analytic hierarchy process (AHP) used in multi-criteria decision analysis.
In systems engineering, software engineering, and computer science, a function model or functional model is a structured representation of the functions within the modeled system or subject area.
Decision-making software is software for computer applications that help individuals and organisations make choices and take decisions, typically by ranking, prioritizing or choosing from a number of options.
In decision-making, a rank reversal is a change in the rank ordering of the preferability of alternative possible decisions when, for example, the method of choosing changes or the set of other available alternatives changes. The issue of rank reversals lies at the heart of many debates in decision-making and multi-criteria decision-making, in particular.
SDI Tools is a set of commercial software add-in tools for Microsoft Excel developed and distributed by Statistical Design Institute, LLC., a privately owned company located in Texas, United States.
Expert Choice is decision-making software that is based on multi-criteria decision making.
Criterium DecisionPlus is decision-making software that is based on multi-criteria decision making.
DEX is a qualitative multi-criteria decision analysis (MCDA) method for decision making and is implemented in DEXi software. This method was developed by a research team led by Bohanec, Bratko, and Rajkovič. The method supports decision makers in making complex decisions based on multiple, possibly conflicting, attributes. In DEX, all attributes are qualitative and can take values represented by words, such as “low” or “excellent”. Attributes are generally organized in a hierarchy. The evaluation of decision alternatives is carried out by utility functions, which are represented in the form of decision rules. All attributes are assumed to be discrete. Additionally, they can be preferentially ordered, so that a higher ordinal value represents a better preference.
The following outline is provided as an overview of and topical guide to machine learning. Machine learning is a subfield of soft computing within computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. Such algorithms operate by building a model from an example training set of input observations in order to make data-driven predictions or decisions expressed as outputs, rather than following strictly static program instructions.