Evaluation of Freezing-Induced Changes in Aroma Profiles of Pomegranate Juice by Quantitative Descriptive Sensory Analysis, Gas Chromatography-Mass Spectrometry/Olfactometry, Odor Activity Values, Orthogonal Partial Least Squares-Discriminant Analysis, and Odorant Addition Experiment. [PDF]
FoodsChen Y +6 more
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The Role of Institutional Pressures in Technology Adoption for Low‐Carbon Manufacturing
Business Strategy and the Environment, EarlyView.ABSTRACT Existing research highlights that the adoption of low‐carbon technologies in manufacturing operations is shaped by the external environment. However, limited understanding exists regarding how technology‐related uncertainty interacts with institutional pressures to influence firms' adoption strategies.
Diellza Salihu +2 more
wiley +1 more source
Pediatric obstructive sleep apnea diagnosis: leveraging machine learning with linear discriminant analysis. [PDF]
Front PediatrQin H +16 more
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Business Strategy and the Environment, EarlyView.ABSTRACT The transition toward more sustainable and innovative agricultural systems increasingly relies on the integration of digital and enabling technologies (KETs). Although the technical and productive aspects of these innovations have been widely investigated, consumer acceptance remains less understood, despite its key role in fostering their ...
Giulio Cascone, Giuseppe Timpanaro
wiley +1 more source
Near-Infrared Spectroscopy Combined with Fuzzy Improved Direct Linear Discriminant Analysis for Nondestructive Discrimination of Chrysanthemum Tea Varieties. [PDF]
FoodsZhang J +5 more
europepmc +1 more source
Ada-LT IP: Functional Discriminant Analysis of Feature Extraction for Adaptive Long-Term Wi-Fi Indoor Localization in Evolving Environments. [PDF]
Sensors (Basel)Hailu TG, Guo X, Si H, Li L, Zhang Y.
europepmc +1 more source
Deep IDA: a deep learning approach for integrative discriminant analysis of multi-omics data with feature ranking-an application to COVID-19. [PDF]
Bioinform AdvWang J, Safo SE.
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Sparse Discriminant Analysis [PDF]
Technometrics, 2011 We consider the problem of performing interpretable classification in the high-dimensional setting, in which the number of features is very large and the number of observations is limited. This setting has been studied extensively in the chemometrics literature, and more recently has become commonplace in biological and medical applications.
Line H Clemmensen +2 more
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Nonparametric Discriminant Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1983A nonparametric method of discriminant analysis is proposed. It is based on nonparametric extensions of commonly used scatter matrices. Two advantages result from the use of the proposed nonparametric scatter matrices. First, they are generally of full rank. This provides the ability to specify the number of extracted features desired.
Keinosuke Fukunaga, James M. Mantock
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Discriminant Learning Analysis
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2008Linear discriminant analysis (LDA) as a dimension reduction method is widely used in classification such as face recognition. However, it suffers from the small sample size (SSS) problem when data dimensionality is greater than the sample size, as in images where features are high dimensional and correlated. In this paper, we propose to address the SSS
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