9 resultados para Ensembles de niveau

em Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco


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El contenido de este trabajo deriva del proyecto de investigación UE-1998-23, «Oferta y Demanda de Formación en Gestión Empresarial para Directivos en la CAPV» y del contrato de investigación «Análisis de la Oferta de Formación en Gestión y en Gestión del Conocimiento». El proyecto era perteneciente a la convocatoria de 1998 de ayudas del Gobierno Vasco a Proyectos de Investigación e Innovacion Tecnológica entre Universidades y Empresas, en su elaboración y desarrollo participaron la Universidad del País Vasco-Euskal Herriko Unibertsitatea, la Universidad de Deusto (ESTE) y el Cluster del Conocimiento, como empresa.

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[EN]A survey of Canadian retail beef was undertaken with emphasis on the trans fatty acid (TFA) and conjugated linoleic acid (CLA) isomers, and compared with current health recommendations. Thirty striploin steaks were collected in the winter and summer from major grocery stores in Calgary (Alberta, Canada). Steak fatty acid compositions (backfat and longissimus lumborum muscle analysed separately) showed minor seasonal differences with lower total saturates (PB0.05) and higher total monounsaturates (PB 0.01) in winter, but no differences in total polyunsaturated fatty acids. The ratio of n-6 and n-3 polyunsaturated fatty acid in longissimus lumborum averaged 5.8. The average TFA content in longissimus lumborum was 0.128 g 100 g_1 serving size, and 10t-18:1 was found to be the predominant isomer (32% of total trans), while vaccenic acid was second most abundant (15% of total trans). The CLA content in longissimus lumborum was similar to that of backfat, ranging from 0.43 to 0.60% of total fatty acids and rumenic acid represented 60% of total isomers. Overall, there is still room for improvement in the saturated, mono- and polyunsaturated fatty acid composition of Canadian beef to meet general dietary guidelines for human consumption and additional targets should include reducing 10t-18:1 while increasing both rumenic and vaccenic acids.

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(FR)Ce texte reprend la question de la compréhension de lecture et la faible note que nos étudiants du secondaire donnent à ce secteur, d’après PISA. De plus en plus de voix s’élèvent pour réclamer que la compréhension de lecture soit une des tâches de tous les professeurs et plus seulement des professeurs de langue et littérature. Lors de la préparation au métier d’enseignant, de plus en plus de cours sont organisés en rapport avec cette question de plus en plus préoccupante dans ce secteur. Les données sont celles-ci et toutes les tentatives pour résoudre ce problème semblent insuffisantes si on ne reprend pas la question au niveau du Curriculum et si on prépare les professeurs aux stratégies de lecture pour que les élèves parviennent à être des lecteurs compétents.

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Homenaje a Georges Laplace, realizado en Vitoria-Gasteiz el 13, 14 y 15 de noviembre de 2012. Edición a cargo de Aitor Calvo, Aitor Sánchez, Maite García-Rojas y Mónica Alonso-Eguíluz

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Homenaje a Georges Laplace, realizado en Vitoria-Gasteiz el 13, 14 y 15 de noviembre de 2012. Edición a cargo de Aitor Calvo, Aitor Sánchez, Maite García-Rojas y Mónica Alonso-Eguíluz.

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This document aims to describe an update of the implementation of the J48Consolidated class within WEKA platform. The J48Consolidated class implements the CTC algorithm [2][3] which builds a unique decision tree based on a set of samples. The J48Consolidated class extends WEKA’s J48 class which implements the well-known C4.5 algorithm. This implementation was described in the technical report "J48Consolidated: An implementation of CTC algorithm for WEKA". The main, but not only, change in this update is the integration of the notion of coverage in order to determine the number of samples to be generated to build a consolidated tree. We define coverage as the percentage of examples of the training sample present in –or covered by– the set of generated subsamples. So, depending on the type of samples that we use, we will need more or less samples in order to achieve a specific value of coverage.

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The CTC algorithm, Consolidated Tree Construction algorithm, is a machine learning paradigm that was designed to solve a class imbalance problem, a fraud detection problem in the area of car insurance [1] where, besides, an explanation about the classification made was required. The algorithm is based on a decision tree construction algorithm, in this case the well-known C4.5, but it extracts knowledge from data using a set of samples instead of a single one as C4.5 does. In contrast to other methodologies based on several samples to build a classifier, such as bagging, the CTC builds a single tree and as a consequence, it obtains comprehensible classifiers. The main motivation of this implementation is to make public and available an implementation of the CTC algorithm. With this purpose we have implemented the algorithm within the well-known WEKA data mining environment http://www.cs.waikato.ac.nz/ml/weka/). WEKA is an open source project that contains a collection of machine learning algorithms written in Java for data mining tasks. J48 is the implementation of C4.5 algorithm within the WEKA package. We called J48Consolidated to the implementation of CTC algorithm based on the J48 Java class.