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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Journal ArticleDOI
Towards improving the efficiency of the fuzzy cognitive map classifier
TL;DR: Comparative experiments showed that the proposed approach makes the FCM a very competitive alternative to other state-of-the-art classifiers.
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A Novel Computerized Tool to Stratify Risk in Carotid Atherosclerosis Using Kinematic Features of the Arterial Wall
Aimilia Gastounioti,Stavros Makrodimitris,Spyretta Golemati,Nikolaos P.E. Kadoglou,Christos D. Liapis,Konstantina S. Nikita +5 more
TL;DR: The incorporation of kinematic features of the arterial wall in CAD seems to have a particularly favorable impact on the performance of image-data-driven diagnosis for CA, which remains to be further elucidated in future prospective studies on large datasets.
Journal ArticleDOI
Sparse random networks with LTP learning rules approximate Bayes classifiers via Parzen's method
TL;DR: The resulting network implements Parzen's method for approximating a Bayes classifier, and can be generalized to include a class of networks including one that adds an input layer of neurons resulting in changes to the kernel used in the Parzen method.
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Statistical learning approach for predicting specific pharmacodynamic, pharmacokinetic, or toxicological properties of pharmaceutical agents
TL;DR: The strategies, current progresses, and the underlying difficulties and future prospects of the application of the recently explored statistical learning methods are discussed.
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Supervised signal detection for adverse drug reactions in medication dispensing data
TL;DR: In this article, a supervised machine learning (SML) method was proposed to detect adverse drug reactions (ADRs) in medication dispensing data. But, the authors did not compare the performance of SML with Sequence Symmetry Analysis (SSA) and SSA.
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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