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Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 105 for “"Linear discriminant analysis"”.
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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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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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Using NMR spectroscopy and linear discriminant analysis to molecular profile varietal honey
… (“fingerprints”) and combined them with linear discriminant analysis (LDA) to predict the varietal, country, and region of varietal honey. As a part of the project, we investigated whether an adjustment to the spectral data based on a signal-to-noise cutoff would provide better predictive …
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Analytic Study of Performance of Error Estimators for Linear Discriminant Analysis with Applications in Genomics
… and mixed moments, in the context of the Linear Discriminant Analysis (LDA) classification rule. In the first part of this dissertation, we obtain the joint sampling distribution of the actual and estimated errors under a general parametric Gaussian assumption. Exact results are provided …
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Performance Evaluation of Logistic Regression, Linear Discriminant Analysis, and Classification and Regression Trees Under Controlled Conditions
<p>Logistic Regression (LR), Linear Discriminant Analysis (LDA), and Classification and Regression Trees (CART) are common classification techniques for prediction of group membership. Since these methods are applied for similar purposes with different procedures, it is important to evaluate the …
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System Design, Construction, Implementation, and Validation For Rapid Single-Cell Classification Using Imaging Multivariate Optical Computing
… optical trapping instrument built in house. Linear discriminant analysis (LDA) has been used to classify individual phytoplankton cells based on the fluorescence excitation spectra for individual cells in the wavelength range 350-650 nm. Interference filters called multivariate optical …
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Utilization of the Wisconsin card sorting test in the diagnostic discrimination of Attention-Deficit/Hyperactivity Disorder and learning disorders in children
… differences between groups. A subsequent cluster analysis was conducted using Ward's method to determine group membership of the subjects and resulted in a sample of 87. This cluster analysis resulted in a four cluster solution with the groups being identified as ADHD, RD-LD, Normal, and "Close …
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Acoustic Feature Design for Speech Recognition, a Statistical Information-Theoretic Approach
… part of this work we present a generalization of linear discriminant analysis (LDA) that optimizes a discriminative criterion and solves the problem in the lower-dimensional subspace. We start with showing that the calculation of the LDA projection matrix is a maximum mutual information estimation …
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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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Data Analysis for Emotion Identification in Text
… emotional sentences in an article using data analysis technologies. Two types of methods are proposed to solve the problem. A straightforward method of identifying emotional sentences is to formulate it as a classification problem. A classifier based on Linear Discriminant Analysis (LDA) is …
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Anomaly detection in hyperspectral signatures using automated derivative spectroscopy methods
… extraction, (2) feature reduction through linear discriminant analysis, (3) performance characterization through receiver operating characteristic curves, and (4) signature classification using nearest mean and maximum likelihood classifiers. The Hyperspectral database contained signatures …
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Detecting anomalies in remotely sensed hyperspectral signatures via wavelet transforms
… feature scalar through the process of linear discriminant analysis. Signature classification is determined by nearest mean criterion that is used to assign each input signature to one of two classes, no target present or target present. Classification accuracy ranged from nearly 60% …
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Heavy minerals of the Cretaceous Hell Creek and Paleocene Ludlow Formations of Slope and Bowman counties, North Dakota
… the Hell Creek and Ludlow Formations using linear discriminant analysis. The comparisons between the heavy mineral percentages of the concretions and surrounding sediments within the Hell Creek and Ludlow Formations showed no significant differences. The comparison of the concretions of the …
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Effects of discrete wavelet compression on automated mammographic shape recognition
… and the shape features are extracted. Second, linear discriminant analysis is used to compute the weightings of the features. Third, a minimum distance Euclidean classifier and the leave-one-out test method is used for classification. Lastly, a two dimensional compression is performed on the …
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Data fusion techniques for biomedical informatics and clinical decision support
… modalities to facilitate enhanced visualization, analysis, detection, estimation, or classification. Data fusion can be applied at the raw-data, feature-based, and decision-based levels. Data fusion applications of different sorts have been built up in areas such as statistics, computer vision and …
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Using Geovisual Analytics to investigate the performance of Geographically Weighted Discriminant Analysis
Geographically Weighted Discriminant Analysis (GWDA) is a method for prediction and analysis of categorical spatial data. It is an extension of Linear Discriminant Analysis (LDA) that allows the relationship between the predictor variables and the categories to vary spatially. This is also referred …
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Quantifying prehension in persons with stroke post rehabilitation
This study describes the analysis of reaching and grasping abilities of the hemiparetic arm and hand of patients post stroke after a series of interactive virtual reality (VR) simulated training sessions and conventional physical therapy of similar intensity. Six subjects participated in VR …
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Synthesizing a Hybrid Benchmark Suite with BenchPrime
… presents BenchPrime, an automated benchmark analysis toolset that is systematic and extensible to analyze the similarity and diversity of benchmark suites. BenchPrime takes multiple benchmark suites and their evaluation metrics as inputs and generates a hybrid benchmark suite comprising only …
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Classification of Human Postural and Gestural Movements Using Center of Pressure Parameters Derived From Force Platforms
… for classification-guided feature extraction. Linear classifiers such as Fisher's Linear Discriminant analysis classifier and nonlinear classifiers such as nearest neighbor classifiers, support vector machines (SVM), and neural networks were explored and successfully applied to the …
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Terrain identification methods for planetary exploration rovers
… phase. Real-time terrain classification uses linear discriminant analysis in the frequency domain to identify gross terrain classes such as sand, gravel, or clay. The algorithm is experimentally validated on a laboratory testbed and on a rover in outdoor conditions. Results demonstrate the …
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