Results 21 to 30 of about 111,184 (298)
Predicting software analysis process risks using linear stepwise discriminant analysis : Statistical methods [PDF]
, 2015 The aim of this work is to introduce the linear stepwise discriminant analysis model to predict software risks in software analysis development process. These methods were used to measure and predict risks by using control techniques.
Abu Naser, Samy S. +3 more
core +1 more source
Face Recognition Using Simplified Probabilistic Linear Discriminant Analysis
International Journal of Advanced Robotic Systems, 2012 Face recognition in uncontrolled environments remains an open problem that has not been satisfactorily solved by existing recognition techniques.
Boštjan Vesnicer +3 more
doaj +1 more source
Semi-supervised linear discriminant analysis [PDF]
, 2011 Fisher's linear discriminant analysis is one of the most commonly used and studied classification methods in chemometrics. The method finds a projection of multivariate data into a lower dimensional space so that the groups in the data are well separated.
Downey, Gerard +5 more
core +4 more sources
Local Feature Discriminant Projection [PDF]
, 2016 In this paper, we propose a novel subspace learning algorithm called Local Feature Discriminant Projection (LFDP) for supervised dimensionality reduction of local features.
Zhen, Xiantong +3 more
core +1 more source
Linear discriminant analysis: A detailed tutorial [PDF]
AI Communications, 2017 Linear Discriminant Analysis (LDA) is a very common technique for dimensionality reduction problems as a pre-processing step for machine learning and pattern classification applications. At the same time, it is usually used as a black box, but (sometimes) not well understood.
Alaa Tharwat +3 more
openaire +1 more source
Comparative Performance of Several Robust Linear Discriminant Analysis Methods
Revstat Statistical Journal, 2007 The problem of the non-robustness of the classical estimates in the setting of the quadratic and linear discriminant analysis has been addressed by many authors: Todorov et al. [19, 20], Chork and Rousseeuw [1], Hawkins and McLachlan [4], He and Fung [5]
Valentin Todorov , Ana M. Pires
doaj +1 more source
Zernike Moments Based Handwritten Pashto Character Recognition Using Linear Discriminant Analysis
Mehran University Research Journal of Engineering and Technology, 2021 This paper presents an efficient Optical Character Recognition (OCR) system for offline isolated Pashto characters recognition. Developing an OCR system for handwritten character recognition is a challenging task because of the handwritten characters ...
Sardar Jehangir +4 more
doaj +1 more source
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
Linear discriminant analysis in network traffic modeling
Tongxin xuebao, 2005 It was not easy to give an accurate judgment of whether the traffic model fitting the actual traffic. The common method was to compare the Hurst parameter, data histogram and autocorrelation function.
ZHANG Bing-yi +3 more
doaj +2 more sources
Cross View Gait Recognition Using Joint-Direct Linear Discriminant Analysis
Sensors, 2016 This paper proposes a view-invariant gait recognition framework that employs a unique view invariant model that profits from the dimensionality reduction provided by Direct Linear Discriminant Analysis (DLDA).
Jose Portillo-Portillo +7 more
doaj +1 more source