نتایج جستجو برای: lda
تعداد نتایج: 5888 فیلتر نتایج به سال:
Standard LDA model suffers the problem that the topic assignment of each word is independent and word correlation hence is neglected. To address this problem, in this paper, we propose a model called Word Related Latent Dirichlet Allocation (WR-LDA) by incorporating word correlation into LDA topic models. This leads to new capabilities that standard LDA model does not have such as estimating in...
Linear Discriminant Analysis (LDA) is a popular feature extraction technique for face image recognition and retrieval. However, It often suffers from the small sample size problem when dealing with the high dimensional face data. Two-step LDA (PCA+LDA) [1–3] is a class of conventional approaches to address this problem. But in many cases, these LDA classifiers are overfitted to the training set...
In face recognition, LDA often encounters the so-called small sample size (SSS) problem, also known as curse of dimensionality. This problem occurs when the dimensionality of the data is quite large in comparison to the number of available training images. One of the approaches for handling this situation is the subspace LDA. It is a two-stage framework: it first uses PCA-based method for dimen...
Recently a kind of matrix-based discriminant feature extraction approach called 2DLDA have been drawn much attention by researchers. 2DLDA can avoid the singularity problem and has low computational costs and has been experimentally reported that 2DLDA outperforms traditional LDA. In this paper, we compare 2DLDA with LDA in view of the discriminant power and find that 2DLDA as a kind of special...
OBJECTIVES The objectives of this study are to examine the efficacy and safety of low-dose aspirin (LDA) vs LDA plus low-intensity warfarin (LDA + W) in the primary thrombosis prevention of aPL-positive patients with SLE and/or obstetric morbidity and the role of clinical and serological markers in the development of thrombosis. METHODS In this 5-year prospective, randomized, open, controlled...
The identification and discrimination of 2 closely related and morphologically similar species of Gyrodactylus, G. salaris and G. thymalli, were assessed using the statistical classification methodologies Linear Discriminant Analysis (LDA) and k-Nearest Neighbours (KNN). These statistical methods were applied to morphometric measurements made on the gyrodactylid attachment hooks. The mean estim...
Source-normalised Linear Discriminant Analysis (SNLDA) was recently introduced to improve speaker recognition using i-vectors extracted from multiple speech sources. SNLDA normalises for the effect of speech source in the calculation of the between-speaker covariance matrix. Sourcenormalised-and-weighted (SNAW) LDA computes a weighted average of source-normalised covariance matrices to better e...
We calculate the electronic structure of several atoms and small molecules by direct minimization of the Self-Interaction Corrected Local Density Approximation (SIC-LDA) functional. To do this we rst derive an expression for the gradient of this functional under the constraint that the orbitals be orthogonal and show that previously given expressions do not correctly incorporate this constraint...
In latent Dirichlet allocation (LDA), topics are multinomial distributions over the entire vocabulary. However, the vocabulary usually contains many words that are not relevant in forming the topics. We adopt a variable selection method widely used in statistical modeling as a dimension reduction tool and combine it with LDA. In this variable selection model for LDA (vsLDA), topics are multinom...
We calculate the electronic structure of several atoms and small molecules by direct minimization of the self-interaction-corrected–local-density-approximation ~SIC-LDA! functional. To do this, we first derive an expression for the gradient of this functional under the constraint that the orbitals be orthogonal and then show that previously given expressions do not correctly incorporate this co...
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