Search results for "Logical matrix"

showing 3 items of 3 documents

BMaD – A Boolean Matrix Decomposition Framework

2014

Boolean matrix decomposition is a method to obtain a compressed representation of a matrix with Boolean entries. We present a modular framework that unifies several Boolean matrix decomposition algorithms, and provide methods to evaluate their performance. The main advantages of the framework are its modular approach and hence the flexible combination of the steps of a Boolean matrix decomposition and the capability of handling missing values. The framework is licensed under the GPLv3 and can be downloaded freely at http://projects.informatik.uni-mainz.de/bmad.

Matrix (mathematics)Theoretical computer scienceAnd-inverter graphBoolean circuitDecomposition (computer science)Logical matrixCircuit minimization for Boolean functionsRepresentation (mathematics)Standard Boolean modelMathematics
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Multi-label classification using boolean matrix decomposition

2012

This paper introduces a new multi-label classifier based on Boolean matrix decomposition. Boolean matrix decomposition is used to extract, from the full label matrix, latent labels representing useful Boolean combinations of the original labels. Base level models predict latent labels, which are subsequently transformed into the actual labels by Boolean matrix multiplication with the second matrix from the decomposition. The new method is tested on six publicly available datasets with varying numbers of labels. The experimental evaluation shows that the new method works particularly well on datasets with a large number of labels and strong dependencies among them.

Multi-label classificationMatrix (mathematics)ComputingMethodologies_PATTERNRECOGNITIONComputer sciencebusiness.industryBoolean matrix multiplicationLogical matrixPattern recognitionArtificial intelligencebusinessClassifier (UML)Sparse matrixProceedings of the 27th Annual ACM Symposium on Applied Computing
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A Mlp-Based Digit And Uppercase Characters Recognition System

1997

A simple software solution for digit and uppercase handwritten characters recognition is presented. The proposed solution is based on a two-layer Multi Layer Perceptron (MLP) trained by a conjugate gradient descent (CGD) optimization algorithm. This neural network is embedded in a software tool for automatic processing of forms achieved using a scanner. The chosen solutions allow us to obtain good results both in terms of recognition rate and speed. In the paper are fully described design details and experimental results.

ScannerArtificial neural networkComputer sciencebusiness.industrySpeech recognitionNumerical digitComputingMethodologies_PATTERNRECOGNITIONSoftwareSimple (abstract algebra)Computer Science::Computer Vision and Pattern RecognitionMultilayer perceptronConjugate gradient methodLogical matrixbusiness
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