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Journal ArticleDOI

Probabilistic neural networks

Donald F. Specht
- 01 Jan 1990 - 
- Vol. 3, Iss: 1, pp 109-118
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.

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Citations
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Journal ArticleDOI

Probabilistic neural networks and the polynomial Adaline as complementary techniques for classification

TL;DR: Two methods for classification based on the Bayes strategy and nonparametric estimators for probability density functions are reviewed and the polynomial equivalent can be found.
Journal ArticleDOI

Deterministic annealing EM algorithm

TL;DR: A deterministic annealing EM (DAEM) algorithm for maximum likelihood estimation problems to overcome a local maxima problem associated with the conventional EM algorithm is presented and can obtain better estimates free of the initial parameter values.
Journal ArticleDOI

Improved binary PSO for feature selection using gene expression data

TL;DR: Improved binary particle swarm optimization (IBPSO) is used in this study to implement feature selection, and the K-nearest neighbor (K-NN) method serves as an evaluator of the IBPSO for gene expression data classification problems, showing that this method effectively simplifies feature selection and reduces the total number of features needed.
Journal ArticleDOI

Use of multiattribute transforms to predict log properties from seismic data

TL;DR: A new method for predicting well‐log properties from seismic data, which is a linear or nonlinear transform between a subset of the attributes and the target log values, is described.
Journal ArticleDOI

Artificial Neural Networks applied to landslide susceptibility assessment

TL;DR: In this article, two different ANNs, used in classification problems, were set up and applied: one belonging to the category of Multi-Layered Perceptron (MLP) and the other to the Probabilistic Neural Network (PNN) family.
References
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Journal ArticleDOI

Nearest neighbor pattern classification

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.

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.