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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Prediction of biological targets using probabilistic neural networks and atom-type descriptors.
TL;DR: Combination of PNN and atom-type descriptors provides a powerful way to predict biological activities from structural information, much more quickly than widely used neural networks such as a feed-forward neural network with error back-propagation.
Journal ArticleDOI
Effects of strong ground motion on the susceptibility of gully type debris flows
TL;DR: In this paper, the authors selected three regions which suffered a ground motion class of 5, 6, and 7 on the Richter scale during the Chi-Chi earthquake as study areas to map the gully-type debris flows that took place after Typhoons Herb and Toraji, respectively.
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Predictive mapping of seabed cover types using angular response curves of multibeam backscatter data: Testing different feature analysis approaches
TL;DR: In this paper, the angular response curves of multibeam backscatter data are used to predict the distributions of seven seabed cover types in an acoustically-complex area of the continental shelf of Western Australia.
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Contributions to Automatic Target Recognition Systems for Underwater Mine Classification
TL;DR: A reasonable construction of the basic belief assignment (BBA) is proposed, which considers both the reliability of the classifiers and the support of individual classifiers provided to the hypotheses about the types of test objects.
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Hidden Markov models for cancer classification using gene expression profiles
TL;DR: The proposed combination between the modified AHP and HMM is a powerful tool for cancer classification and useful as a real clinical decision support system for medical practitioners.
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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