998 resultados para Continuous classes


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Model trees are a particular case of decision trees employed to solve regression problems. They have the advantage of presenting an interpretable output, helping the end-user to get more confidence in the prediction and providing the basis for the end-user to have new insight about the data, confirming or rejecting hypotheses previously formed. Moreover, model trees present an acceptable level of predictive performance in comparison to most techniques used for solving regression problems. Since generating the optimal model tree is an NP-Complete problem, traditional model tree induction algorithms make use of a greedy top-down divide-and-conquer strategy, which may not converge to the global optimal solution. In this paper, we propose a novel algorithm based on the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to globally near-optimal solutions. We call our new approach evolutionary model tree induction (E-Motion). We test its predictive performance using public UCI data sets, and we compare the results to traditional greedy regression/model trees induction algorithms, as well as to other evolutionary approaches. Results show that our method presents a good trade-off between predictive performance and model comprehensibility, which may be crucial in many machine learning applications. (C) 2010 Elsevier Inc. All rights reserved.

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El conjunto eficiente en la Teoría de la Decisión Multicriterio juega un papel fundamental en los procesos de solución ya que es en este conjunto donde el decisor debe hacer su elección más preferida. Sin embargo, la generación de tal conjunto puede ser difícil, especialmente en problemas continuos y/o no lineales. El primer capítulo de esta memoria, es introductorio a la Decisión Multicriterio y en él se exponen aquellos conceptos y herramientas que se van a utilizar en desarrollos posteriores. El segundo capítulo estudia los problemas de Toma de Decisiones en ambiente de certidumbre. La herramienta básica y punto de partida es la función de valor vectorial que refleja imprecisión sobre las preferencias del decisor. Se propone una caracterización del conjunto de valor eficiente y diferentes aproximaciones con sus propiedades de encaje y convergencia. Varios algoritmos interactivos de solución complementan los desarrollos teóricos. El tercer capítulo está dedicado al caso de ambiente de incertidumbre. Tiene un desarrollo parcialmente paralelo al anterior y utiliza la función de utilidad vectorial como herramienta de modelización de preferencias del decisor. A partir de la consideración de las distribuciones simples se introduce la eficiencia en utilidad, su caracterización y aproximaciones, que posteriormente se extienden a los casos de distribuciones discretas y continuas. En el cuarto capítulo se estudia el problema en ambiente difuso, aunque de manera introductoria. Concluimos sugiriendo distintos problemas abiertos.---ABSTRACT---The efficient set of a Multicriteria Decicion-Making Problem plays a fundamental role in the solution process since the Decisión Maker's preferred choice should be in this set. However, the computation of that set may be difficult, specially in continuous and/or nonlinear problems. Chapter one introduces Multicriteria Decision-Making. We review basic concepts and tools for later developments. Chapter two studies Decision-Making problems under certainty. The basic tool is the vector valué function, which represents imprecisión in the DM's preferences. We propose a characterization of the valué efficient set and different approximations with nesting and convergence properties. Several interactive algorithms complement the theoretical results. We devote Chapter three to problems under uncertainty. The development is parallel to the former and uses vector utility functions to model the DM's preferences. We introduce utility efficiency for simple distributions, its characterization and some approximations, which we partially extend to discrete and continuous classes of distributions. Chapter four studies the problem under fuzziness, at an exploratory level. We conclude with several open problems.

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The use of transmission matrices and lumped parameter models for describing continuous systems is the subject of this study. Non-uniform continuous systems which play important roles in practical vibration problems, e.g., torsional oscillations in bars, transverse bending vibrations of beams, etc., are of primary importance.

A new approach for deriving closed form transmission matrices is applied to several classes of non-uniform continuous segments of one dimensional and beam systems. A power series expansion method is presented for determining approximate transmission matrices of any order for segments of non-uniform systems whose solutions cannot be found in closed form. This direct series method is shown to give results comparable to those of the improved lumped parameter models for one dimensional systems.

Four types of lumped parameter models are evaluated on the basis of the uniform continuous one dimensional system by comparing the behavior of the frequency root errors. The lumped parameter models which are based upon a close fit to the low frequency approximation of the exact transmission matrix, at the segment level, are shown to be superior. On this basis an improved lumped parameter model is recommended for approximating non-uniform segments. This new model is compared to a uniform segment approximation and error curves are presented for systems whose areas very quadratically and linearly. The effect of varying segment lengths is investigated for one dimensional systems and results indicate very little improvement in comparison to the use of equal length segments. For purposes of completeness, a brief summary of various lumped parameter models and other techniques which have previously been used to approximate the uniform Bernoulli-Euler beam is a given.

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The classes of continuous-time flows on Rn×p that induce the same flow on the set of p- dimensional subspaces of Rn×p are described. The power flow is briefly reviewed in this framework, and a subspace generalization of the Rayleigh quotient flow [Linear Algebra Appl. 368C, 2003, pp. 343-357] is proposed and analyzed. This new flow displays a property akin to deflation in finite time. © 2008 Yokohama Publishers.

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This study investigates how the experiences of Junior Infants are shaped in multigrade classes. Multigrade classes are composed of two or more grades within the same classroom with one teacher having responsibility for the instruction of all grades in this classroom within a time-tabled period (Little, 2001, Mason and Doepner, 1998). The overall aim of the research is to problematize the issues of early childhood pedagogy in multigrade classes in the context of children negotiating identities, positioning and power relations. A Case Study approach was employed to explore the perspectives of the teachers, children and their parents in eight multigrade schools. Concurrent with this, a nation-wide Questionnaire Survey was also conducted which gave a broader context to the case study findings. Findings from the research study suggest that institutional context is vitally important and finding the space to implement pedagogic practices is a highly complex matter for teachers. While a majority of teachers reported the benefits for younger children being in mixed-age settings alongside older children, only a minority of case study school teachers demonstrated how it is possible to promote classroom climates which were provided multiple opportunities for younger children to engage fully in classrooms. The findings reveal constraints on pedagogical practice which included: time pressures within the job, an increase in diversity in pupil population, meeting special needs, large class sizes, high pupil/teacher ratios, and planning/organisation of tasks which intensified the complexities of addressing the needs of children who differ significantly in age, cognitive, social and emotional levels. An emergent and recurrent theme of this study is the representation of Junior Infants as apprentices in their ‘communities of practice’ who contributed in peripheral ways to the practices of their groups (Lave and Wenger, 1991, Wenger, 1998). Through a continuous process of negotiation of meaning, these pupils learned the knowledge and skills within their communities of practice that empowered some to participate more fully than others. The children in their ‘figured worlds’ (Holland, Lachiotte, Skinner and Caine 1998) occupy identities which are influenced by established arrangements of resources and practices within that community as well as by their own agentive actions. Finally, the findings of the study also demonstrate how the dimension of power is central to the exercise of social relations and pedagogical practices in multigrade classes.

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Most psychophysical studies of object recognition have focussed on the recognition and representation of individual objects subjects had previously explicitely been trained on. Correspondingly, modeling studies have often employed a 'grandmother'-type representation where the objects to be recognized were represented by individual units. However, objects in the natural world are commonly members of a class containing a number of visually similar objects, such as faces, for which physiology studies have provided support for a representation based on a sparse population code, which permits generalization from the learned exemplars to novel objects of that class. In this paper, we present results from psychophysical and modeling studies intended to investigate object recognition in natural ('continuous') object classes. In two experiments, subjects were trained to perform subordinate level discrimination in a continuous object class - images of computer-rendered cars - created using a 3D morphing system. By comparing the recognition performance of trained and untrained subjects we could estimate the effects of viewpoint-specific training and infer properties of the object class-specific representation learned as a result of training. We then compared the experimental findings to simulations, building on our recently presented HMAX model of object recognition in cortex, to investigate the computational properties of a population-based object class representation as outlined above. We find experimental evidence, supported by modeling results, that training builds a viewpoint- and class-specific representation that supplements a pre-existing repre-sentation with lower shape discriminability but possibly greater viewpoint invariance.

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We provide a complete isomorphic classification of the Banach spaces of continuous functions on the compact spaces 2(m) circle plus [0, alpha], the topological sums of Cantor cubes 2(m), with m smaller than the first sequential cardinal, and intervals of ordinal numbers [0, alpha]. In particular, we prove that it is relatively consistent with ZFC that the only isomorphism classes of C(2(m) circle plus [0, alpha]) spaces with m >= N(0) and alpha >= omega(1) are the trivial ones. This result leads to some elementary questions on large cardinals.

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After a decade of rapid expansion in Australian higher education, student numbers have grown considerably in many courses and subjects, especially at the undergraduate level.
Larger class sizes pose significant teaching challenges, not least in the assessment of student learning. Perhaps most troubling, large classes may limit the amount of feedback provided to students.
In response to the pressures and challenges of assessing larger groups of students, academic staff are responding through:
• greater attention to the communication of clear assessment criteria to students;
• the development and use of marking guides to be used by teaching and assessing teams;
• the increasing use of various forms of exemplars to guide student efforts — as well as to guide marking and grading — including the modelling of discipline-based thinking, writing and performance; and
• the continuous refinement and dissemination of assessment policy and practice in relation to large student groups.
The issue of workload is central in any decisions about assessment of large classes for it is a serious one for students and staff alike. Staff teaching large student groups invariably undertake an informal, qualitative weighing-up of the efficiency of assessment tasks vis-à-vis their educational effectiveness.
There is little doubt that establishing an effective assessment program — developing criteria, guides, exemplars and models; discussing and refining them and communicating them to students and other staff — will have an initial negative impact on workload for staff with coordinating responsibilities.
However, this preparatory work is likely to lead to three gains. The first is a reduction in the time required for marking due to a higher quality of student submission. The second is a resolution of some of the potential issues likely when many staff are involved in marking and grading, through a streamlining of marking and grading practices. Finally, the availability of clear, transparent criteria and examples of work will contribute positively to the overall quality of teaching and learning.

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Monoidal logic, ML for short, which formalized the fuzzy logics of continuous t-norms and their residua, has arisen great interest, since it has been applied to fuzzy mathematics, artificial intelligence, and other areas. It is clear that fuzzy logics basically try to represent imperfect or fuzzy information aiming to model the natural human reasoning. On the other hand, in order to deal with imprecision in the computational representation of real numbers, the use of intervals have been proposed, as it can guarantee that the results of numerical computation are in a bounded interval, controlling, in this way, the numerical errors produced by successive roundings. There are several ways to connect both areas; the most usual one is to consider interval membership degrees. The algebraic counterpart of ML is ML-algebra, an interesting structure due to the fact that by adding some properties it is possible to reach different classes of residuated lattices. We propose to apply an interval constructor to ML-algebras and some of their subclasses, to verify some properties within these algebras, in addition to the analysis of the algebraic aspects of them

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Na Análise do Comportamento, vários estudos são realizados a fim de entender como comportamentos podem produtivamente ser controlados por eventos arbitrariamente relacionados, através da formação classes de equivalência. A inclusão de estímulos reforçadores nas classes tem sido apontada como um possível facilitador de sua formação. O presente estudo teve como objetivos avaliar a formação de classes de equivalência mediada por estímulos reforçadores específicos em crianças que apresentam baixo rendimento escolar. Usando crianças com desenvolvimento típico e em maior número, comparado com a literatura, pretendeu-se obter dados com menor variabilidade intersujeitos que é comumente encontrada nesse tipo de pesquisa. Para isso, foram utilizados reforçadores específicos com quatorze crianças (no Experimento I) que apresentam dificuldades de aprendizagem. O procedimento do Experimento 1 foi dividido em 10 fases. Em todas as fases, houve reforçadores específicos (frutas ou brinquedos) para cada uma das classes potenciais que se pretendia verificar. Inicialmente foi realizado um treino de pareamento por identidade com os estímulos dos Conjuntos A (A I e A2), B (B 1 e B2) e C (C I e C2) com reforçamento contínuo, seguido do mesmo treino com Reforçamento Intermitente. Logo após esses treinos foram realizados os testes de relações emergentes AB/BA, ACICA e BCICB. Antes de cada teste foi feito o retorno às discriminações de linha de base. Os dados do Experimento I evidenciam grande variabilidade intersujeitos nos testes de formação de classes. O Experimento 2 pretendeu investigar o efeito de dois tipos de pré-treino sobre o desempenho nos testes de formação de classes. Foi realizado com seis crianças e subdividido em dois grupos. O Grupo I foi submetido a um pré-treino de pareamento por identidade e o Grupo 2 a um pré-treino de pareamento arbitrário. Os resultados confirmam parcialmente a hipótese de que pré-treino de pareamento arbitrário pode reduzir a variabilidade inter-sujeitos nesse tipo estudos, pois altas taxas de variabilidade persistem no presente estudo. .Estudos posteriores deverão explorar essa possibilidade mais sistematicamente.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)