A false acceptance error controlling method for hyperspherical classifiers
نویسندگان
چکیده
منابع مشابه
A false acceptance error controlling method for hyperspherical classifiers
Controlling false acceptance errors is of critical importance in many pattern recognition applications, including signature and speaker veri$cation problems. Toward this goal, this paper presents two post-processing methods to improve the performance of hyperspherical classi$ers in rejecting patterns from unknown classes. The $rst method uses a self-organizational approach to design minimum rad...
متن کاملMaximum Margin Classifiers with Specified False Positive and False Negative Error Rates
This paper addresses the problem of maximum margin classification given the moments of class conditional densities and the false positive and false negative error rates. Using Chebyshev inequalities, the problem can be posed as a second order cone programming problem. The dual of the formulation leads to a geometric optimization problem, that of computing the distance between two ellipsoids, wh...
متن کاملAn effective method for controlling false discovery and false nondiscovery rates in genome-scale RNAi screens.
In most genome-scale RNA interference (RNAi) screens, the ultimate goal is to select siRNAs with a large inhibition or activation effect. The selection of hits typically requires statistical control of 2 errors: false positives and false negatives. Traditional methods of controlling false positives and false negatives do not take into account the important feature in RNAi screens: many small-in...
متن کاملReducing False Acceptance Rate in Offline Writer Independent Signature Verification System through Ensemble of Classifiers
Handwritten signature verification is a very challenging and critical task. This work aims at proposing an efficient offline handwritten signature verification model using writer independent approach. The prime focus of this work is on reducing the false acceptance rate of genuine signatures of writers while letting false rejection rate at a satisfactory level through ensemble of classifiers. T...
متن کاملA New Oscillating-Error Technique for Classifiers
This paper describes a new method for reducing the error in a classifier. It uses a weight adjustment update, but includes the very simple rule of either adding or subtracting the adjustment, based on whether the data point is currently larger or smaller than the desired value, and on a pointby-point basis. This gives added flexibility to the convergence procedure, where through a series of tra...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Neurocomputing
سال: 2004
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2003.10.008