نتایج جستجو برای: latent data
تعداد نتایج: 2449036 فیلتر نتایج به سال:
Background and Objective: Approximately, half of the occupational accidents are associated with the construction industry in Iran. Therefore, the factor analysis of risk variables affecting occupational injuries in the construction industry can lead to understanding and reducing the rate of injuries in these projects. The purpose of this study was to identify the risk factors affecting the type...
The members of Mycobacterium tuberculosis complex (MTBC) known as causative agents of human tuberculosis. Tuberculosis infection is one of the most important occupational risks for healthcare workers (HCWs) in most countries, such as Iran. In general, there are two types of tuberculosis, they include: latent infection and active TB. Latent tuberculosis infection (LTBI) means: a patient is infec...
One means to support for design-by-analogy (DbA) in practice involves giving designers efficient access to source analogies as inspiration to solve problems. The patent database has been used for many DbA support efforts, as it is a preexisting repository of catalogued technology. Latent Semantic Analysis (LSA) has been shown to be an effective computational text processing method for extractin...
We propose a novel method for inferring whether X causes Y or vice versa from joint observations of X and Y . The basic idea is to model the observed data using probabilistic latent variable models, which incorporate the effects of unobserved noise. To this end, we consider the hypothetical effect variable to be a function of the hypothetical cause variable and an independent noise term (not ne...
Describing the dimension reduction (DR) techniques by means of probabilistic models has recently been given special attention. Probabilistic models, in addition to a better interpretability of the DR methods, provide a framework for further extensions of such algorithms. One of the new approaches to the probabilistic DR methods is to preserving the internal structure of data. It is meant that i...
The conference that this book builds upon contained many different special topics within the general area of modeling with categorical latent variables, also referred to as mixture modeling. The many different models addressed at that conference and within this volume may overwhelm a newcomer to the field. In fact, however, there are really only a small number of variations on a common theme. T...
Unsupervised learning on imbalanced data is challenging because, when given imbalanced data, current model is often dominated by the major category and ignores the categories with small amount of data. We develop a latent variable model that can cope with imbalanced data by dividing the latent space into a shared space and a private space. Based on Gaussian Process Latent Variable Models, we pr...
Most of estimation of distribution algorithms (EDAs) try to represent explicitly the relationship between variables with factorization techniques or with graphical models such as Bayesian networks. In this paper, we propose to use latent variable models such as Helmholtz machine and probabilistic principal component analysis for capturing the probabilistic distribution of given data. The latent...
Restricted Boltzmann Machines (RBMs) are an important class of latent variable models for representing vector data. An under-explored area is multimode data, where each data point is a matrix or a tensor. Standard RBMs applying to such data would require vectorizing matrices and tensors, thus resulting in unnecessarily high dimensionality and at the same time, destroying the inherent higher-ord...
Latent variable models exist with continuous, categorical, or both types of latent variables. The role of latent variables is to account for systematic patterns in the observed responses. This article has two goals: (a) to establish whether, based on observed responses, it can be decided that an underlying latent variable is continuous or categorical, and (b) to quantify the effect of sample si...
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