BR: A New Method for Computing All Typical Testors

Abstract. Typical testors are a useful tool for both feature selection and for determining feature relevance in supervised classication problems. Nowadays, generating all typical testors of a training matrix is computationally expensive; all reported algorithms have exponential complexity, depending mainly on the number of columns in the training matrix. For this reason, different approaches such as sequential and parallel algorithms, genetic algorithms and hardware implementations techniques have been developed. In this paper, we introduce a fast implementation of the algorithm CT EXT (which is one of the fastest algorithms reported) based on an accumulative binary tuple, developed for generating all typical testors of a training matrix. The accumulative binary tuple implemented in the CT EXT algorithm, is a useful way to simplifies the search of feature combinations which fulfill the testor property, because its implementation decreases the number of operations involved in the process of generating all typical testors. In addition, experimental results using the proposed fast implementation of the CT EXT algorithm and the comparison with other state of the art algorithms that generated typical testors are presented.

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“…Follow the notation used in [5]. Let V = (a 1 , a 2 , · · · , a u ) be a binary u-tuple of elements, a i ∈ {0, 1}, i = 1, · · · , u.…”

Section: Basic Conceptsmentioning

confidence: 99%

A Fast Implementation of the CT_EXT Algorithm for the Testor Property Identification

Sánchez-Díaz

Piza-Davila

Lazo-Cortés

et al. 2010

Advances in Soft Computing

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“…20 ) are not shown. This is because we were not endowed with the source code of the BR implementation as we kindly requested to the authors, but only with an application which is unable to read previously-defined DM and BM; instead, it works with randomly-generated ones.…”

Section: Methodsmentioning

confidence: 99%

“…Follow the notation used in (Ref. 20 ), let V = (a 1 , a 2 , · · · , a u ) be a binary u-tuple of elements, a i ∈ {0, 1}, i = 1, · · · , u. The column corresponding to a feature x i ∈ BM is a binary u-tuple, denoted by V x i , whose cardinality is the number of rows in BM.…”

Section: Definitions and Propositions Of Fast Implementation Of Ct Exmentioning

confidence: 99%

“…24,27,28,8,29,19,20 ). All of these algorithms can be classified into groups: internal-type and external-type algorithms.…”

Section: Algorithms For Computing Typical Testorsmentioning

confidence: 99%

“…29 ) and BR (Ref. 20 ). The CT EXT algorithm incrementally, generates feature combinations by reducing step by step the number of objects belonging to different classes that are confused, until a combination that satisfy testor property is obtained.…”

Section: The Fast Implementation Of the Ct-ext Algorithmmentioning

confidence: 99%

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A Fast Implementation for the Typical Testor Property Identification Based on an Accumulative Binary Tuple

Sánchez-Díaz¹,

Lazo-Cortés²,

Piza-Davila³

2012

IJCIS

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In this paper, we introduce a fast implementation of the CT EXT algorithm for testor property identification, that is based on an accumulative binary tuple. The fast implementation of the CT EXT algorithm (one of the fastest algorithms reported), is designed to generate all the typical testors from a training matrix, requiring a reduced number of operations. Experimental results using this fast implementation and the comparison with other state-of-the-art algorithms that generate typical testors are presented.

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