An Algorithm for Computing Typical Testors Based on Elimination of Gaps and Reduction of Columns

Lias-Rodríguez, Alexsey; Sánchez-Díaz, Guillermo

doi:10.1142/s0218001413500225

Cited by 19 publications

(17 citation statements)

References 8 publications

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“…For each row, the cell containing the shortest runtime is highlighted. Tables 2 and 3 present similar comparisons, but using sintetics basic matrices obtained from previously works as [21] and [26], respectively. OOM indicates an Out of Memory Error occurred during the execution, whereas NF means that the algorithm did not finish its execution in less than a week.…”

Section: Experiments and Resultsmentioning

confidence: 90%

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An Algorithm for Computing Minimum-Length Irreducible Testors

et al. 2020

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In pattern recognition, the elimination of unnecessary and/or redundant attributes is known as feature selection. Irreducible testors have been used to perform this task. An objective of the Minimum Description Length Principle (MDL) applied to feature selection in pattern recognition and data mining is to select the minimum number of attributes in a data set. Consequently, the MDL principle leads us to consider the subset of irreducible testors of minimum length. Some algorithms that find the whole set of irreducible testors have been reported in the literature. However, none of these algorithms was designed to generate only minimum-length irreducible testors. In this paper, we propose the first algorithm specifically designed to calculate all minimum-length irreducible testors from a training sample. The paper presents some experimental results obtained using synthetic and real data in which the performance of the proposed algorithm is contrasted with other state-of-the-art algorithms that were adapted to generate only irreducible testers of minimum length. INDEX TERMS Feature selection, MDL principle, minimum-length irreducible testors, testor.

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Section: Experiments and Resultsmentioning

confidence: 90%

“…The exhaustive algorithms take exponential time in the number of features. Some examples of these algorithms include the following: Lex [39], all-NRD [7], Fast-CT-EXT [37], YYC [3], Fast-BR [21], and Parallel-YYC [27]. These algorithms can be easily adapted to return only minimumlength irreducible testors.…”

Section: Related Workmentioning

confidence: 99%

An Algorithm for Computing Minimum-Length Irreducible Testors

et al. 2020

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“…Descubrir estrategias que logren cada vez un mejor rendimiento en el descubrimiento de los testores típicos puede ser vital para encontrar la solución óptima de un problema dado de reconocimiento de patrones. LEX, CT-EXT y Fast-BR son algunos de los algoritmos más destacados actualmente ante tales fines [16][17][18].…”

Section: Confusiónunclassified

Selección de variables relacionadas con fallos de chumaceras aplicando reconocimiento lógico combinatorio de patrones

Gómez

Montero

Gomez-Mancilla

2020

Ingeniare. Rev. chil. ing.

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En el diagnóstico de fallos de chumaceras actualmente no se considera el conocimiento experto expresado en variables no numéricas, a pesar de constituir una fuente de información importante. Este trabajo se desarrolló con el objetivo de identificar los rasgos más relevantes para clasificar un grupo de fallos ocurridos en las chumaceras de una turbina de vapor. Las variables que soportan el trabajo corresponden a los datos almacenados en reportes de diagnóstico y mantenimiento de una termoeléctrica en explotación. Las técnicas aplicadas para procesar los datos cuantitativos y cualitativos son herramientas de reconocimiento lógico combinatorio de patrones (RLCP). Se determinó la confusión de los rasgos del conjunto inicial y posteriormente los testores y testores típicos, y se calculó el peso informacional de los rasgos. Los resultados alcanzados mostraron que la relevancia de los rasgos cualitativos presentes en la descripción de los fallos es superior a la de los rasgos numéricos típicamente empleados.

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“…Algorithms addressing the search of all TTs must run as faster as possible [18][19][20][21][22][23][24]. Various strategies have been developed to reach this goal, for example, the application of hardware and software-hardware configurations [25,26].…”

Section: Introductionmentioning

confidence: 99%

“…The new RoPM algorithm allows for the computation of all TTs in short runtimes, regardless the complexity of the problem. In many situations, the proposed algorithm is capable to exhibit better performances than the fastest algorithms (fast-BR and GCreduct [20,21,24]), especially when achieving a significant reduction of runtimes is required. In particular, GCreduct is an algorithm that allows for the search of reducts (from the rough set theory) and TTs [21,24].…”

Section: Introductionmentioning

confidence: 99%

RoPM: An Algorithm for Computing Typical Testors Based on Recursive Reductions of the Basic Matrix

et al. 2021

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Feature selection plays an important role in pattern recognition and smart computing. The full set of typical testors constitutes a useful tool for solving feature selection problems, especially those problems in which the objects are described by both quantitative and qualitative features. However, finding the typical testors involves a high computational cost. That is why even the most efficient methods become unsuitable to solve some problems. In this work, a new algorithm was introduced in order to reduce the long runtimes involved in the search of typical testors. The performance of the proposed algorithm was evaluated by means of several tests, which use both real-world and simulation data. MATLAB and Java language on Eclipse SDK platform were used to build the simulation dataset and to perform the tests, respectively. The runtimes achieved by the proposed algorithm were significantly shorter than those obtained by fast-BR and GCreduct (the two fastest algorithms) mainly when the latter ones exhibited excessively long runtimes.

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An Algorithm for Computing Typical Testors Based on Elimination of Gaps and Reduction of Columns

Cited by 19 publications

References 8 publications

An Algorithm for Computing Minimum-Length Irreducible Testors

An Algorithm for Computing Minimum-Length Irreducible Testors

Selección de variables relacionadas con fallos de chumaceras aplicando reconocimiento lógico combinatorio de patrones

RoPM: An Algorithm for Computing Typical Testors Based on Recursive Reductions of the Basic Matrix

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