discrete data
Using Discrete Data of ECG in the Numerical and Spectral forms
... a discrete signal of the amplitude strain versus time duration was ...the discrete data in a cycle would result in values from the peak amplitude, meanwhile the time transition method would produce ...
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Reaping the Benefits of Discrete Data Capture: Decreased Paper, Increased Satisfaction, Improved Data Quality
... on data sharing and advanced analytics to understand and analyze patient populations in order to find new ways to improve care and remain ...the data will aid conformity to care standards and business best ...
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Identification of continuous-time models for nonlinear dynamic systems from discrete data
... from discrete data, but this often involves the reconstruction of the derivatives of variables from the discrete data (Coca & Billings, ...of discrete time models as a first step ...
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The selection of optimal discriminant procedures for discrete data
... This chapter introduces the main issues of discriminant analysis when applied to discrete data. It has been kept non technical, but, nevertheless, intends to introduce the main issues of discriminant ...
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Rational approximation of discrete data with asymptomatic behaviour
... This thesis is concerned with the least-squares approximation of discrete data that appear to exhibit asymptotic behaviour. In particular, we consider using rational functions as they are able to display a ...
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Current status of discrete data capture in synoptic surgical pathology and cancer reporting
... synoptic data to be included in all pathology reports in their centers, and by the CAP to include a cancer checklist requirement in their inspection checklists have done much to make this practice as routine as it ...
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Testing Conditional Independence on Discrete Data using Stochastic Complexity
... Testing for conditional independence is a core aspect of constraint-based causal discovery. Although commonly used tests are perfect in theory, they often fail to reject independence in practice, especially when ...
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Pattern extraction and clustering for high-dimensional discrete data
... approximation data obtained by all these methods still contain negative and non-binary values, from which it is hard to deduce useful information to help understand the original binary ...for discrete ...
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Bayesian Biclustering on Discrete Data: Variable Selection Methods
... Categorical data, a type of discrete data sometimes called nominal data, is a statistical data type whose value is one of a number of fixed ...categorical data is the color of ...
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Using Spline Functions to Smooth Discrete Data
... An acceptable approximation (smoothing) curve is obtained only after five sub-intervals, i.e., six connecting points. In this case the error of the approximation is about 4.5%. The error of the approximation will ...
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EVOLUTIONARY CLUSTERING ALGORITHM FOR DISCRETE DATA
... In brief, the proposed GA based clustering algorithm has several useful features: (i) it uses an entropy based, rather than the distance based, similarity measure for clustering; (ii) since the fitness measure is ...
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Aspects of forecasting aggregate and discrete data
... The answer is that this will be possible, whenever the following two conditions are satisfied assuming we do not have to worry about the initial information about the state; for example,[r] ...
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Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks
... The proposed architecture is a " neural network" implementation of a graphical model where all the variables are observed in the training set, with the hidden units p[r] ...
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Three-dimensional Radial Visualization of High-dimensional Continuous or Discrete Data
... A number of aspects of our development could benefit from further attention. For instance, the MRP is a linear projection method that is designed to maximize separation between grouped data. It would be ...
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Bayesian Methods for Nonlinear and Discrete Data with Complex Dependence.
... the data or problem at hand, this may be ...observed data as possible, but there is an inherent trade off between the quality and quantity of the collected ...generating data for ABC from ...
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Survey on Anomalous Topic Discovery in Discrete Data
... The data is typically comprised of records defined over several dimensions such as user ID, amount spent, time between consecutive card usage, and so ...complete data available and also have labeled ...
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The estimation of continuous-time systems using discrete data
... first half of the period apart from an annual cycle, and then shows a gradual upward trend. Thus apart from the model being invalid our stationarity assumptions are contravened. Because of the likely absence of high ...
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Discrete longitudinal data modeling with a mean correlation regression approach
... longitudinal discrete responses (Diggle et ...longitudinal data via PACs and marginal variances, and Gaskins, et ...binary data (Muenz and Rubinstein, 1985), the working model ap- proach (Zeger et ...
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New method for denoising borehole transient electromagnetic data with discrete wavelet transform
... simple data sets, the residual is caused mainly by the noise retained in the unprocessed detail ...survey data with repeated measurements, the residual is mainly because of distorted transients in the raw ...
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Discrete optimization methods to fit piecewise affine models to data points
... We observe that, as expected, the fitting error over the training sets decreases monotonically for larger values of k. As to the generalization error, computed, by definition, on the validation set, it achieves the ...
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