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Showing 1 to 20 of 1049 for “"Discriminant"”.
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Linear discriminant analysis
Linear discriminant analysis is the classification of an individual as having arisen from one or the other of two populations on the basis of a scalar linear function of measurements of the individual. This paper is a population and large sample study of linear discriminant analysis. The population …
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Classification and discriminant analysis
… Three major techniques of classification and discriminant analysis are presented: linear discriminant analysis, quadratic discriminant procedures and logistic regression. Logistic regression is reviewed in its general framework and as a classification tool. A few articles on the comparison of …
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Agricultural loan evaluation with discriminant analysis
As each year passes, the farmers' needs for adequate credit adapted to their particular type of businesses, become more evident, The shift in the past half century to a mechanized agriculture has greatly increased farm credit needs. The total real estate assets of farmers have increased from a low …
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Selected topics in statistical discriminant analysis.
… consists of three selected topics in statistical discriminant analysis: dimension reduction, regularization methods, and imputation methods. In Chapter 2 we first derive a new linear dimension-reduction method to determine a low-dimensional hyperplane that preserves or nearly preserves the …
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Modified Discriminant Analysis of School Organizations
Made available in DSpace on 2014-12-05T22:27:18Z (GMT). No. of bitstreams: 1 0009039.pdf: 5205040 bytes, checksum: 6fa724539b07661a633dd2e8b9c5a610 (MD5) Previous issue date: 1954
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Penalized discriminant analysis for multivariate functional data
We introduce a penalized discriminant analysis method for multivariate functional data supported on compact 1D domains, motivated by an application that aims to identify subjects with poor cognitive status from diffusion MRI data. By leveraging a connection to the optimal scoring problem, we bypass …
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A Comparison of the Classification Accuracy of Linear and Quadratic Statistical Discriminant Models versus Linear and Quadratic Programming Discriminant Models
… models versus traditional statistical discriminant analysis. Monte Carlo techniques were used to compute population 1, population 2, and average misclassification rates for the linear discriminant function (LDF), the quadratic discriminant function (QDF), a linear programming …
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Unified Framework for Matrix-Variate Linear Discriminant Analysis
The linear discriminant analysis (LDA) is a feature extractor used in classification of high-dimensional data in a wide range of applications. In the classification of matrix-variate data, LDA can be used on the vectorized representation of the data in the commonly called one-dimensional LDA …
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Dynamic Discriminant Analysis with Applications in Computational Surgery
… fields has been impeded by the lack of a dynamic discriminant analysis technique capable of classifying data given systems with overwhelming similarity. Methods: Four new machine learning algorithms were developed (DLS, DPP, RELIEF-RBF, and Intent Vectors). These algorithms were then applied to …
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Discriminant function analysis for categorization of best practices
… performance classification models using multiple discriminant function analyses that divide project cost and schedule performance into four groups. The study will examine the best practices that discriminate the most among these four groups. These results are then summarized into a best practice …
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The Use of Predictive Composites in Multiple Discriminant Analysis
Made available in DSpace on 2014-12-12T19:53:32Z (GMT). No. of bitstreams: 1 7606825.pdf: 4340940 bytes, checksum: 017989d72a2e333a0af3702681056458 (MD5) Previous issue date: 1975
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Aberrant self-promotion versus Machiavellianism: a discriminant validity study
… of the present study was to provide evidence of discriminant validity for the aberrant self-promotion construct proposed by Gustafson and Ritzer (1994a). The study attempted to differentiate the aberrant self-promotion construct from the Machiavellianism construct proposed by Christie (1970a). …
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The discriminant — From a quadratic equation to dynamic nonlinear systems
… students don't understand the potential of the discriminant. Usually discussed while learning the Quadratic Formula to solve quadratic equations, students learn its use for the classification of type and number of solutions for each equation being solved. Most students memorize the formula, …
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Efficient enumeration of extensions of local fields with bounded discriminant
… the number of extensions of a given degree and discriminant. Following his work, we present an algorithm for the computation of generating polynomials for all extensions K / k of a given degree and discriminant. We also present canonical sets of generating polynomials of extensions of degree p m …
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Design and simulation of a highly discriminant laser array waveguide
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.
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A discriminant model for classifying contractor performance on public works projects
… (i.e. Z2 model) was developed. Multivariate discriminant analysis is used to classify contractors' past performance into good and poor groups. The classification model is made up of 5 variables: (i) contractors' plant and equipment resources; (ii) past performance in time on similar projects; …
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Identifying the Dimensions of Integrity: A Confirmatory and Discriminant Validity Analysis
… item analysis, confirmatory factor analysis, discriminant validity analysis, and an analysis of social desirability to test the validity of the five integrity dimensions identified by Green (1999): Concern for Others, Conscientiousness, Emotional Control, Fairness, and Honesty. Results …
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