Results 31 to 40 of about 279,382 (273)
Sensible functional linear discriminant analysis [PDF]
Computational Statistics & Data Analysis, 2018 The focus of this paper is to extend Fisher's linear discriminant analysis (LDA) to both densely re-corded functional data and sparsely observed longitudinal data for general $c$-category classification problems. We propose an efficient approach to identify the optimal LDA projections in addition to managing the noninvertibility issue of the covariance
Lu-Hung Chen, Ci-Ren Jiang
openaire +2 more sources
Applied SciencesColorectal cancer is one of the most commonly diagnosed cancers in developed countries. Although the gold-standard diagnosis technique is the histological analysis of colon biopsies, it is important to investigate different diagnostic tools because the ...
Maria Lasalvia +2 more
doaj +1 more source
Dimensionality reduction of clustered data sets [PDF]
, 2008 We present a novel probabilistic latent variable model to perform linear dimensionality reduction on data sets which contain clusters. We prove that the maximum likelihood solution of the model is an unsupervised generalisation of linear discriminant ...
Sanguinetti, G.
core +2 more sources
A Doubly Regularized Linear Discriminant Analysis Classifier With Automatic Parameter Selection
IEEE Access, 2021 Linear discriminant analysis (LDA) based classifiers tend to falter in many practical settings where the training data size is smaller than, or comparable to, the number of features.
Alam Zaib +3 more
doaj +1 more source
Implicitly Constrained Semi-Supervised Linear Discriminant Analysis
, 2014 Semi-supervised learning is an important and active topic of research in pattern recognition. For classification using linear discriminant analysis specifically, several semi-supervised variants have been proposed.
Krijthe, Jesse H., Loog, Marco
core +1 more source
Molecular Oncology, EarlyView.We developed and validated a DNA methylation–based biomarker panel to distinguish pleural mesothelioma from other pleural conditions. Using the IMPRESS technology, we translated this panel into a clinically applicable assay. The resulting two classifier models demonstrated excellent performance, achieving high AUC values and strong diagnostic accuracy.
Janah Vandenhoeck +12 more
wiley +1 more source
PERBANDINGAN ANALISIS DISKRIMINAN LINIER KLASIK DAN ANALISIS DISKRIMINAN LINIER ROBUST UNTUK PENGKLASIFIKASIAN KESEJAHTERAAN MASYARAKAT KABUPATEN/KOTA DI JAWA TENGAH [PDF]
, 2013 Discriminant analysis is a statistics method which is used to classify an individual or object into certain group which has determined based on its independent variables.
KARTIKAWATI, ANA
core +2 more sources
OFFLINE LINEAR DISCRIMINANT ANALYSIS CLASSFICATION OF TWO CLASS EEG SIGNALS
Iraqi Journal of Information & Communication Technology, 2019 This paper investigates the use of LDA algorithm In the EEG classification. EEG feature extraction is Implemented to reduce the dimensionality of data. The Sliding Window Technique (SWT) is used to calculate the mean within each window samples.
Haider A. Abdulkareem +1 more
doaj +1 more source
Weighted LDA techniques for I-vector based speaker verification [PDF]
, 2012 This paper introduces the Weighted Linear Discriminant Analysis (WLDA) technique, based upon the weighted pairwise Fisher criterion, for the purposes of improving i-vector speaker verification in the presence of high intersession variability.
Dean, David +5 more
core +3 more sources
Molecular Oncology, EarlyView.Nanosecond infrared laser (NIRL) low‐volume sampling combined with shotgun lipidomics uncovers distinct lipidome alterations in oropharyngeal squamous cell carcinoma (OPSCC) of the palatine tonsil. Several lipid species consistently differentiate tumor from healthy tissue, highlighting their potential as diagnostic markers.
Leonard Kerkhoff +11 more
wiley +1 more source