The generalized Nash equilibrium problem (GNEP) is often difficult to solve by Newton-type method... more The generalized Nash equilibrium problem (GNEP) is often difficult to solve by Newton-type methods since the problem tends to have locally nonunique solutions. Here we take an existing trust-region method which is known to be locally fast convergent under a relatively mild error bound condition, and modify this method by a nonmonotone strategy in order to obtain a more reliable and efficient solver. The nonmonotone trust-region method inherits the nice local convergence properties of its monotone counterpart and is also shown to have the same global convergence properties. Numerical results indicate that the nonmonotone trust-region method is significantly better than the monotone version, and is at least competitive to an existing software applied to the same reformulation used within our trust-region framework. Additional tests on quasi-variational inequalities (QVI) are also presented to validate efficiency of the proposed extension.
In the ancient world, the chasm caused by earthquakes was considered as a passage between the wor... more In the ancient world, the chasm caused by earthquakes was considered as a passage between the world of the dead and that of the living. The paper aims to investigate this dystopian imagery in Latin poetry: the Nachleben of a famous Iliadic passage will be explored firstly in Latin epic (Virgil, Ovid, Silius Italicus and Statius) and then in a different and, in a sense, unexpected work, the didactic poem of Lucretius. In this respect, particular attention will be given to how Latin poets re-elaborate this imagery: in fact, they do not limit themselves to work over Homer’s text, but they also make reference to intermediary texts, according to a literary technique which has been defined as «window reference».
At Statius, silv. IV 7, 1 the paradosis sociata has long been suspected of being corrupt: the mos... more At Statius, silv. IV 7, 1 the paradosis sociata has long been suspected of being corrupt: the most recent editors print the humanistic conjecture spatiata. This note aims at defending the MSS reading as an example of those \u2018flights\u2019 which are at the center of Pindarus\u2019 poetry, the Greek model explicitly invoked by Statius
IEEE Transactions on Neural Networks and Learning Systems, 2021
Truncated Newton (TN) methods have been a useful technique for large-scale optimization. Instead ... more Truncated Newton (TN) methods have been a useful technique for large-scale optimization. Instead of obtaining the full Newton direction, a truncated method approximately solves the Newton equation with an inner Conjugate Gradient (CG) procedure (TNCG for the whole method). These methods have been employed to efficiently solve linear classification problems. But even in this deeply studied field, various theoretical and numerical aspects were not completely explored. The first contribution of this work is to comprehensively study the global and local convergence when TNCG is applied to linear classification. Because of the lack of twice differentiability under some losses, many past works cannot be applied here. We prove various missing pieces of theory from scratch and clarify many proper references. The second contribution is to study the termination of the CG method. For the first time when TNCG is applied to linear classification, we show that the inner stopping condition strongly affects the convergence speed. We propose using a quadratic stopping criterion to achieve both robustness and efficiency. The third contribution is that of combining the study on inner stopping criteria with that of preconditioning. We discuss how convergence theory is affected by preconditioning and finally propose an effective preconditioned TNCG.
A pesquisa abordou sobre as reflexões da educação ambiental presentes nos Relatórios de Conclusão... more A pesquisa abordou sobre as reflexões da educação ambiental presentes nos Relatórios de Conclusão do Curso Técnico em Meio Ambiente do Instituto Federal Sul Rio-Grandense, Campus Pelotas - Visconde da Graça, durante os anos de 2015 a 2018. Com este objetivo esta pesquisa analisou a presença ou ausência de concepções de educação ambiental, que estão vinculadas à ética. Pesquisou-se em que medida as concepções acadêmicas conferem a educação ambiental reflexões significativas e quais suas articulações com relação à ética considerando os conceitos ambientais formulados por pesquisadores que contribuíram para a nossa compreensão de ser-estar no mundo. A metodologia de pesquisa bibliográfica utilizada possuiu uma abordagem quali-quantitativa observando-se como resultados que, nos trabalhos analisados, 37 possuíam conceitos de educação ambiental enquanto que 17 não apresentaram estes conceitos, ou seja, 68,51% dos trabalhos continham concepções de educação ambiental, com temas diversos com...
We conjecture that players' behavior is more and more correlated with the match outcome as the 90... more We conjecture that players' behavior is more and more correlated with the match outcome as the 90 minutes elapse. We demonstrate the effect of this elapsing-time bias by applying a host of machine learning techniques on a large corpus of finely detailed football matches of European leagues. We show that we can predict the output of a match with high confidence simply by looking at the last 15 minutes of the game. We design a new task and we show that is not affected by elapsing-time bias.
O presente trabalho apresenta as “Considerações sobre as áreas verdes através do olhar dos freque... more O presente trabalho apresenta as “Considerações sobre as áreas verdes através do olhar dos frequentadores da Praça Coronel Pedro Osório”, estudo realizado na cidade de Pelotas/RS. A Praça Coronel Pedro Osório foi o local escolhido para a aplicação de um questionário, que contou com a participação de 50 transeuntes e/ou frequentadores do local. A questão que norteou a pesquisa foi: qual o entendimento que os frequentadores da praça têm sobre as áreas verdes da cidade? A hipótese trabalhada era que os espaços de áreas verdes urbanos contribuem para várias melhorias nos quesitos social, mental e ambiental, além de uma melhor socialização entre as pessoas na cidade e com a natureza. A pesquisa teve como objetivo geral verificar a importância das áreas verdes no contexto urbano através dos frequentadores da praça. O estudo contou com uma metodologia descritiva através de uma abordagem quali-quantitativa. Com os dados obtidos, notou-se que o espaço verde, tendo condições adequadas para se...
Esta pesquisa avaliou a abordagem sobre educação ambiental (EA) nos trabalhos de conclusão do Cur... more Esta pesquisa avaliou a abordagem sobre educação ambiental (EA) nos trabalhos de conclusão do Curso Técnico em Meio Ambiente do Instituto Federal de Educação, Ciência e Tecnologia Sul-rio-grandense, Campus Pelotas – Visconde da Graça (IFSul Pelotas-CaVG), realizados nos anos de 2011 a 2014. Como questionamento este trabalho procurou esclarecer se é possível encontrar abordagens de EA vinculadas à ética no contexto de trabalhos acadêmicos de nível técnico, tentando demonstrar que a educação ambiental e a ética ocorrem através da edificação da educação com base nos valores humanos. A metodologia utilizada foi a pesquisa bibliográfica com abordagem quali-quantitativa. A pesquisa apresentou como justificativa o fato de vivenciarmos uma era de fragilidade humana, que necessita de reflexão sobre as práticas cotidianas, por este motivo objetivou-se reconhecer que existe necessidade de criarmos uma cultura acadêmica que estimule o estudo, a pesquisa e a produção científica que sirva de bas...
In this work we propose a general framework that provides a unified convergence analysis for nonm... more In this work we propose a general framework that provides a unified convergence analysis for nonmonotone decomposition algorithms. The main motivation to embed nonmonotone strategies within a decomposition approach lies in the fact that enforcing the reduction of the objective function could be unnecessarily expensive, taking into account that groups of variables are individually updated. We define different search directions and line searches satisfying the conditions required by the presented nonmonotone decomposition framework to obtain global convergence. We employ a set of large-scale network equilibrium problems as a computational example to show the advantages of a nonmonotone algorithm over its monotone counterpart. In conclusion, a new smart implementation for decomposition methods has been derived to solve numerical issues on large-scale partially separable functions.
Recent advances in pharmacogenomics have generated a wealth of data of different types whose anal... more Recent advances in pharmacogenomics have generated a wealth of data of different types whose analysis have helped in the identification of signatures of different cellular sensitivity/resistance responses to hundreds of chemical compounds. Among the different data types, gene expression has proven to be the more successful for the inference of drug response in cancer cell lines. Although effective, the whole transcriptome can introduce noise in the predictive models, since specific mechanisms are required for different drugs and these realistically involve only part of the proteins encoded in the genome. We analyzed the pharmacogenomics data of 961 cell lines tested with 265 anti-cancer drugs and developed different machine learning approaches for dissecting the genome systematically and predict drug responses using both drug-unspecific and drug-specific genes. These methodologies reach better response predictions for the vast majority of the screened drugs using tens to few hundred...
In liberalized markets, there usually exists a day-ahead session where energy is sold and acquire... more In liberalized markets, there usually exists a day-ahead session where energy is sold and acquired for the following production day. Owing to the high uncertainty of its production, renewable energy (wind in particular) can significantly influence the network imbalance of the following day. In this work, we consider the problem of predicting the sum of the bid volumes for wind energy of all the producers inside the day-ahead energy market. This is a valuable tool to be used by an energy provider in order to determine the imbalance of a market zone and, thus, properly size its bids. In particular, we focus on the estimation of the possible relationship between the meteorological forecasts and the wind power offered on the market by the companies for a market zone. We propose a machine learning model which is used to compute a 1-day-ahead forecast. The input-output mapping is obtained by support vector regression. The input feature vector is defined by a suitable feature extraction technique since the meteorological forecasts are given on a lattice of thousands of geographical points. The computational experiments are performed considering the Italian market as a case study (years 2012-2016). The results show that the proposed feature extraction technique, selecting only some geographical zones, manages to reduce the error attained using all the features. Moreover, classical statistical methods are shown to be outperformed by machine learning models. The analysis reveals also some weaknesses of the model, which may be due to other nonmeteorological factors at play. KEYWORDS day-ahead forecasting, extreme learning machines (ELMs), feature selection, machine learning, support vector regression (SVR), wind power market 1 INTRODUCTION Over the last few years, there has been an increasing interest in the study of numerical predictive models related to renewable energies, which are a serious alternative to replace traditional energy sources. Renewable energies represent a suitable and economical alternative to conventional power plants, but they are characterized by a high degree of variability. To deal with these uncertainties, several machine learning and feature selection techniques have been adopted for various forecasting tasks related to renewable energy. One of the most important and widely studied problems is the forecasting of energy production of power plants. Machine learning techniques have been widely used to obtain a mapping from weather data, generally wind speed, to the power generated by the turbines of a power plant. In the work of Heinermann and Kramer, 1 2 machine learning models, namely, regression trees and support vector regression (SVR), are combined with an ensemble method. Support vector regression is used also in the work of Zeng and Qiao, 2 where a new kernel, based on the wavelet mother function, is shown to outperform the more commonly used radial basis function kernel. In the work of Wan et al, 3 extreme learning machines (ELMs) are used as a fast and reliable alternative to the more traditional neural networks (NNs). In the work of Ellis et al, 4 a specific analysis of high variability events is carried out by means of random forests and support vector machines (SVMs). In the work of Kusiak et al, 5 Cornejo-Bueno et al, 6 and Taslimi Renani
We analyze the performance drivers for data-driven inventory management in a Newsvendor setting w... more We analyze the performance drivers for data-driven inventory management in a Newsvendor setting with nonstationary demand. For this, we study two novel approaches which are based on machine learning techniques (linear quantile regression and tree-based regression, respectively) and which use historical demand observations and auxiliary data to prescribe optimal inventory quantities. We identify three major performance drivers, that are non-linearity, heteroscedasticity and usability. We evaluate both models both in an extensive simulation experiment where we control different properties of the feature-demand relationship as well as on a complex real-world data set from a restaurant chain. From these experiments we conclude that in situations in which the structure of the feature-demand relationships is not known to be predominantly linear - which can be assumed to be the typical case in practice - we recommend the much more robust tree-based approach. Furthermore, the tree-based also provides comparatively better results for feature-dependent noise, i.e., heteroscedasticity. We also find that in the real-world setting, the tree-based approach performs better with very small data-sets due to the better built-in feature selection which is important in terms of usability in practice.
Revista Bio-grafía: Escritos sobre la biología y su enseñanza, 2012
Entre las décadas de 1930 y 1940 se generó el consenso que dio el origen a la denominada síntesis... more Entre las décadas de 1930 y 1940 se generó el consenso que dio el origen a la denominada síntesis evolutiva. Este consenso presentaba un conjunto teórico de gran riqueza a la vez que se proponía como un programa de investigación para el estudio de la evolución de la vida. Sin embargo, en las últimas décadas algunos aspectos de este conjunto teórico fueron cuestionados, a la vez que otras áreas de investigación fueron incorporadas, dando lugar a una serie de complejos debates de orden diverso. Por otro lado, en relación con el ámbito educativo, existe un amplio acuerdo sobre la necesidad de que la enseñanza secundaria obligatoria garantice un sólido aprendizaje de los modelos y conceptos fundamentales de la biología evolutiva, al tiempo que se reconoce que los resultados, en términos de aprendizaje, son muy deficientes. En dicho contexto surge la cuestión de qué modelos de la biología evolutiva deberían servir como referencia para la enseñanza obligatoria. En este trabajo analizamos diferentes argumentaciones en relación con la inclusión o no de las últimas modificaciones teóricas en la enseñanza de la teoría de la evolución en algunos ámbitos educativos. Con este fin, en una primera instancia analizamos algunas de las principales modificaciones y propuestas teóricas que han tenido lugar en relación con la teoría de la evolución de las últimas décadas. Posteriormente, indagamos algunas de las argumentaciones sobre su posible inclusión en el ámbito educativo. Por último presentamos algunos apuntes finales que hacen más las veces de apertura que de una búsqueda de conclusiones.
En este trabajo se presentan los resultados de una investigación tendiente a identificar los prin... more En este trabajo se presentan los resultados de una investigación tendiente a identificar los principales obstáculos para el aprendizaje del modelo de evolución por selección natural en estudiantes de dos cursos de secundaria. La existencia de dichos obstáculos se infiere a partir de la identificación y caracterización de los patrones explicativos y las concepciones que los estudiantes ponen en juego al explicar casos de evolución adaptativa, así como de análisis provenientes de la historia y epistemología de la biología y de la psicología cognitiva. Se identifican la teleología de sentido común, el razonamiento causal lineal y el razonamiento centrado en el individuo como tres obstáculos principales y se discuten algunas de las implicancias didácticas de estos resultados.
The generalized Nash equilibrium problem (GNEP) is often difficult to solve by Newton-type method... more The generalized Nash equilibrium problem (GNEP) is often difficult to solve by Newton-type methods since the problem tends to have locally nonunique solutions. Here we take an existing trust-region method which is known to be locally fast convergent under a relatively mild error bound condition, and modify this method by a nonmonotone strategy in order to obtain a more reliable and efficient solver. The nonmonotone trust-region method inherits the nice local convergence properties of its monotone counterpart and is also shown to have the same global convergence properties. Numerical results indicate that the nonmonotone trust-region method is significantly better than the monotone version, and is at least competitive to an existing software applied to the same reformulation used within our trust-region framework. Additional tests on quasi-variational inequalities (QVI) are also presented to validate efficiency of the proposed extension.
In the ancient world, the chasm caused by earthquakes was considered as a passage between the wor... more In the ancient world, the chasm caused by earthquakes was considered as a passage between the world of the dead and that of the living. The paper aims to investigate this dystopian imagery in Latin poetry: the Nachleben of a famous Iliadic passage will be explored firstly in Latin epic (Virgil, Ovid, Silius Italicus and Statius) and then in a different and, in a sense, unexpected work, the didactic poem of Lucretius. In this respect, particular attention will be given to how Latin poets re-elaborate this imagery: in fact, they do not limit themselves to work over Homer’s text, but they also make reference to intermediary texts, according to a literary technique which has been defined as «window reference».
At Statius, silv. IV 7, 1 the paradosis sociata has long been suspected of being corrupt: the mos... more At Statius, silv. IV 7, 1 the paradosis sociata has long been suspected of being corrupt: the most recent editors print the humanistic conjecture spatiata. This note aims at defending the MSS reading as an example of those \u2018flights\u2019 which are at the center of Pindarus\u2019 poetry, the Greek model explicitly invoked by Statius
IEEE Transactions on Neural Networks and Learning Systems, 2021
Truncated Newton (TN) methods have been a useful technique for large-scale optimization. Instead ... more Truncated Newton (TN) methods have been a useful technique for large-scale optimization. Instead of obtaining the full Newton direction, a truncated method approximately solves the Newton equation with an inner Conjugate Gradient (CG) procedure (TNCG for the whole method). These methods have been employed to efficiently solve linear classification problems. But even in this deeply studied field, various theoretical and numerical aspects were not completely explored. The first contribution of this work is to comprehensively study the global and local convergence when TNCG is applied to linear classification. Because of the lack of twice differentiability under some losses, many past works cannot be applied here. We prove various missing pieces of theory from scratch and clarify many proper references. The second contribution is to study the termination of the CG method. For the first time when TNCG is applied to linear classification, we show that the inner stopping condition strongly affects the convergence speed. We propose using a quadratic stopping criterion to achieve both robustness and efficiency. The third contribution is that of combining the study on inner stopping criteria with that of preconditioning. We discuss how convergence theory is affected by preconditioning and finally propose an effective preconditioned TNCG.
A pesquisa abordou sobre as reflexões da educação ambiental presentes nos Relatórios de Conclusão... more A pesquisa abordou sobre as reflexões da educação ambiental presentes nos Relatórios de Conclusão do Curso Técnico em Meio Ambiente do Instituto Federal Sul Rio-Grandense, Campus Pelotas - Visconde da Graça, durante os anos de 2015 a 2018. Com este objetivo esta pesquisa analisou a presença ou ausência de concepções de educação ambiental, que estão vinculadas à ética. Pesquisou-se em que medida as concepções acadêmicas conferem a educação ambiental reflexões significativas e quais suas articulações com relação à ética considerando os conceitos ambientais formulados por pesquisadores que contribuíram para a nossa compreensão de ser-estar no mundo. A metodologia de pesquisa bibliográfica utilizada possuiu uma abordagem quali-quantitativa observando-se como resultados que, nos trabalhos analisados, 37 possuíam conceitos de educação ambiental enquanto que 17 não apresentaram estes conceitos, ou seja, 68,51% dos trabalhos continham concepções de educação ambiental, com temas diversos com...
We conjecture that players' behavior is more and more correlated with the match outcome as the 90... more We conjecture that players' behavior is more and more correlated with the match outcome as the 90 minutes elapse. We demonstrate the effect of this elapsing-time bias by applying a host of machine learning techniques on a large corpus of finely detailed football matches of European leagues. We show that we can predict the output of a match with high confidence simply by looking at the last 15 minutes of the game. We design a new task and we show that is not affected by elapsing-time bias.
O presente trabalho apresenta as “Considerações sobre as áreas verdes através do olhar dos freque... more O presente trabalho apresenta as “Considerações sobre as áreas verdes através do olhar dos frequentadores da Praça Coronel Pedro Osório”, estudo realizado na cidade de Pelotas/RS. A Praça Coronel Pedro Osório foi o local escolhido para a aplicação de um questionário, que contou com a participação de 50 transeuntes e/ou frequentadores do local. A questão que norteou a pesquisa foi: qual o entendimento que os frequentadores da praça têm sobre as áreas verdes da cidade? A hipótese trabalhada era que os espaços de áreas verdes urbanos contribuem para várias melhorias nos quesitos social, mental e ambiental, além de uma melhor socialização entre as pessoas na cidade e com a natureza. A pesquisa teve como objetivo geral verificar a importância das áreas verdes no contexto urbano através dos frequentadores da praça. O estudo contou com uma metodologia descritiva através de uma abordagem quali-quantitativa. Com os dados obtidos, notou-se que o espaço verde, tendo condições adequadas para se...
Esta pesquisa avaliou a abordagem sobre educação ambiental (EA) nos trabalhos de conclusão do Cur... more Esta pesquisa avaliou a abordagem sobre educação ambiental (EA) nos trabalhos de conclusão do Curso Técnico em Meio Ambiente do Instituto Federal de Educação, Ciência e Tecnologia Sul-rio-grandense, Campus Pelotas – Visconde da Graça (IFSul Pelotas-CaVG), realizados nos anos de 2011 a 2014. Como questionamento este trabalho procurou esclarecer se é possível encontrar abordagens de EA vinculadas à ética no contexto de trabalhos acadêmicos de nível técnico, tentando demonstrar que a educação ambiental e a ética ocorrem através da edificação da educação com base nos valores humanos. A metodologia utilizada foi a pesquisa bibliográfica com abordagem quali-quantitativa. A pesquisa apresentou como justificativa o fato de vivenciarmos uma era de fragilidade humana, que necessita de reflexão sobre as práticas cotidianas, por este motivo objetivou-se reconhecer que existe necessidade de criarmos uma cultura acadêmica que estimule o estudo, a pesquisa e a produção científica que sirva de bas...
In this work we propose a general framework that provides a unified convergence analysis for nonm... more In this work we propose a general framework that provides a unified convergence analysis for nonmonotone decomposition algorithms. The main motivation to embed nonmonotone strategies within a decomposition approach lies in the fact that enforcing the reduction of the objective function could be unnecessarily expensive, taking into account that groups of variables are individually updated. We define different search directions and line searches satisfying the conditions required by the presented nonmonotone decomposition framework to obtain global convergence. We employ a set of large-scale network equilibrium problems as a computational example to show the advantages of a nonmonotone algorithm over its monotone counterpart. In conclusion, a new smart implementation for decomposition methods has been derived to solve numerical issues on large-scale partially separable functions.
Recent advances in pharmacogenomics have generated a wealth of data of different types whose anal... more Recent advances in pharmacogenomics have generated a wealth of data of different types whose analysis have helped in the identification of signatures of different cellular sensitivity/resistance responses to hundreds of chemical compounds. Among the different data types, gene expression has proven to be the more successful for the inference of drug response in cancer cell lines. Although effective, the whole transcriptome can introduce noise in the predictive models, since specific mechanisms are required for different drugs and these realistically involve only part of the proteins encoded in the genome. We analyzed the pharmacogenomics data of 961 cell lines tested with 265 anti-cancer drugs and developed different machine learning approaches for dissecting the genome systematically and predict drug responses using both drug-unspecific and drug-specific genes. These methodologies reach better response predictions for the vast majority of the screened drugs using tens to few hundred...
In liberalized markets, there usually exists a day-ahead session where energy is sold and acquire... more In liberalized markets, there usually exists a day-ahead session where energy is sold and acquired for the following production day. Owing to the high uncertainty of its production, renewable energy (wind in particular) can significantly influence the network imbalance of the following day. In this work, we consider the problem of predicting the sum of the bid volumes for wind energy of all the producers inside the day-ahead energy market. This is a valuable tool to be used by an energy provider in order to determine the imbalance of a market zone and, thus, properly size its bids. In particular, we focus on the estimation of the possible relationship between the meteorological forecasts and the wind power offered on the market by the companies for a market zone. We propose a machine learning model which is used to compute a 1-day-ahead forecast. The input-output mapping is obtained by support vector regression. The input feature vector is defined by a suitable feature extraction technique since the meteorological forecasts are given on a lattice of thousands of geographical points. The computational experiments are performed considering the Italian market as a case study (years 2012-2016). The results show that the proposed feature extraction technique, selecting only some geographical zones, manages to reduce the error attained using all the features. Moreover, classical statistical methods are shown to be outperformed by machine learning models. The analysis reveals also some weaknesses of the model, which may be due to other nonmeteorological factors at play. KEYWORDS day-ahead forecasting, extreme learning machines (ELMs), feature selection, machine learning, support vector regression (SVR), wind power market 1 INTRODUCTION Over the last few years, there has been an increasing interest in the study of numerical predictive models related to renewable energies, which are a serious alternative to replace traditional energy sources. Renewable energies represent a suitable and economical alternative to conventional power plants, but they are characterized by a high degree of variability. To deal with these uncertainties, several machine learning and feature selection techniques have been adopted for various forecasting tasks related to renewable energy. One of the most important and widely studied problems is the forecasting of energy production of power plants. Machine learning techniques have been widely used to obtain a mapping from weather data, generally wind speed, to the power generated by the turbines of a power plant. In the work of Heinermann and Kramer, 1 2 machine learning models, namely, regression trees and support vector regression (SVR), are combined with an ensemble method. Support vector regression is used also in the work of Zeng and Qiao, 2 where a new kernel, based on the wavelet mother function, is shown to outperform the more commonly used radial basis function kernel. In the work of Wan et al, 3 extreme learning machines (ELMs) are used as a fast and reliable alternative to the more traditional neural networks (NNs). In the work of Ellis et al, 4 a specific analysis of high variability events is carried out by means of random forests and support vector machines (SVMs). In the work of Kusiak et al, 5 Cornejo-Bueno et al, 6 and Taslimi Renani
We analyze the performance drivers for data-driven inventory management in a Newsvendor setting w... more We analyze the performance drivers for data-driven inventory management in a Newsvendor setting with nonstationary demand. For this, we study two novel approaches which are based on machine learning techniques (linear quantile regression and tree-based regression, respectively) and which use historical demand observations and auxiliary data to prescribe optimal inventory quantities. We identify three major performance drivers, that are non-linearity, heteroscedasticity and usability. We evaluate both models both in an extensive simulation experiment where we control different properties of the feature-demand relationship as well as on a complex real-world data set from a restaurant chain. From these experiments we conclude that in situations in which the structure of the feature-demand relationships is not known to be predominantly linear - which can be assumed to be the typical case in practice - we recommend the much more robust tree-based approach. Furthermore, the tree-based also provides comparatively better results for feature-dependent noise, i.e., heteroscedasticity. We also find that in the real-world setting, the tree-based approach performs better with very small data-sets due to the better built-in feature selection which is important in terms of usability in practice.
Revista Bio-grafía: Escritos sobre la biología y su enseñanza, 2012
Entre las décadas de 1930 y 1940 se generó el consenso que dio el origen a la denominada síntesis... more Entre las décadas de 1930 y 1940 se generó el consenso que dio el origen a la denominada síntesis evolutiva. Este consenso presentaba un conjunto teórico de gran riqueza a la vez que se proponía como un programa de investigación para el estudio de la evolución de la vida. Sin embargo, en las últimas décadas algunos aspectos de este conjunto teórico fueron cuestionados, a la vez que otras áreas de investigación fueron incorporadas, dando lugar a una serie de complejos debates de orden diverso. Por otro lado, en relación con el ámbito educativo, existe un amplio acuerdo sobre la necesidad de que la enseñanza secundaria obligatoria garantice un sólido aprendizaje de los modelos y conceptos fundamentales de la biología evolutiva, al tiempo que se reconoce que los resultados, en términos de aprendizaje, son muy deficientes. En dicho contexto surge la cuestión de qué modelos de la biología evolutiva deberían servir como referencia para la enseñanza obligatoria. En este trabajo analizamos diferentes argumentaciones en relación con la inclusión o no de las últimas modificaciones teóricas en la enseñanza de la teoría de la evolución en algunos ámbitos educativos. Con este fin, en una primera instancia analizamos algunas de las principales modificaciones y propuestas teóricas que han tenido lugar en relación con la teoría de la evolución de las últimas décadas. Posteriormente, indagamos algunas de las argumentaciones sobre su posible inclusión en el ámbito educativo. Por último presentamos algunos apuntes finales que hacen más las veces de apertura que de una búsqueda de conclusiones.
En este trabajo se presentan los resultados de una investigación tendiente a identificar los prin... more En este trabajo se presentan los resultados de una investigación tendiente a identificar los principales obstáculos para el aprendizaje del modelo de evolución por selección natural en estudiantes de dos cursos de secundaria. La existencia de dichos obstáculos se infiere a partir de la identificación y caracterización de los patrones explicativos y las concepciones que los estudiantes ponen en juego al explicar casos de evolución adaptativa, así como de análisis provenientes de la historia y epistemología de la biología y de la psicología cognitiva. Se identifican la teleología de sentido común, el razonamiento causal lineal y el razonamiento centrado en el individuo como tres obstáculos principales y se discuten algunas de las implicancias didácticas de estos resultados.
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