Journal ArticleDOI
Probabilistic neural networks
TLDR
A probabilistic neural network that can compute nonlinear decision boundaries which approach the Bayes optimal is formed, and a fourlayer neural network of the type proposed can map any input pattern to any number of classifications.About:
This article is published in Neural Networks.The article was published on 1990-01-01. It has received 3772 citations till now. The article focuses on the topics: Probabilistic neural network & Activation function.read more
Citations
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A comparative analysis of models for predicting delays in air traffic networks
TL;DR: The MJLS model, which is specifically designed to capture aggregate air traffic dynamics, leverages on these factors and outperforms the ANN in predicting the future spatial distribution of delays, and a tradeoff between model simplicity and prediction accuracy is revealed.
Journal ArticleDOI
Neural networks for predicting conditional probability densities: improved training scheme combining EM and RVFL
Dirk Husmeier,John G. Taylor +1 more
TL;DR: By adopting the RVFL concept and constraining a subset of the parameters to randomly chosen initial values (such that the EM-algorithm can be applied), the training process can be accelerated by about two orders of magnitude.
Journal ArticleDOI
A Parzen classifier with an improved robustness against deviations between training and test data
TL;DR: This paper presents a classification method that tries to anticipate slight deviations of the (statistical properties of the) training and the test data (i.e. the data to which the classifier is applied in the operational phase), based on a generalised likelihood function for determining the kernel width of the Parzen classifier.
Journal ArticleDOI
Estimation of break location and size for loss of coolant accidents using neural networks
TL;DR: A probabilistic neural network that has been applied well to the classification problems is used in order to identify the break locations of loss of coolant accidents (LOCA) and estimate their break size accurately.
Journal ArticleDOI
Neural network-based diagnostic and prognostic estimations in breast cancer microscopic instances
TL;DR: This paper deals with breast cancer diagnostic and prognostic estimations employing neural networks over the Wisconsin Breast Cancer datasets, which consist of measurements taken from breast cancer microscopic instances.
References
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Journal ArticleDOI
Nearest neighbor pattern classification
Thomas M. Cover,Peter E. Hart +1 more
TL;DR: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
Journal ArticleDOI
On Estimation of a Probability Density Function and Mode
TL;DR: In this paper, the problem of the estimation of a probability density function and of determining the mode of the probability function is discussed. Only estimates which are consistent and asymptotically normal are constructed.
Book
Introduction to the Theory of Statistics
TL;DR: In this article, a tabular summary of parametric families of distributions is presented, along with a parametric point estimation method and a nonparametric interval estimation method for point estimation.
Journal ArticleDOI
Introduction to the Theory of Statistics.
Jacob Wolfowitz,A. M. Mood +1 more
TL;DR: In this article, a tabular summary of parametric families of distributions is presented, along with a parametric point estimation method and a nonparametric interval estimation method for point estimation.
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