International Journal of Hybrid Intelligent Systems, 2009
Abstract. The margin maximization principle implemented by binary Support Vector Machines (SVMs) ... more Abstract. The margin maximization principle implemented by binary Support Vector Machines (SVMs) has been shown to be equivalent to find the hyperplane equidistant to the closest points belonging to the convex hulls that enclose each class of examples. In this paper, we ...
Abstract. We present a method for image segmentation, that is, to identify image points with an i... more Abstract. We present a method for image segmentation, that is, to identify image points with an indication of the region or class they belong to. The proposed algorithm basically consists of two stages. First it starts by restoring the image from possible contamination. In the ...
2012 IEEE 42nd International Symposium on Multiple-Valued Logic, 2012
In this work, a Takagi-Sugeno-Kang (TSK) model is used for time series analysis and some importan... more In this work, a Takagi-Sugeno-Kang (TSK) model is used for time series analysis and some important questions about the identification of this kind of models are addressed: the identification of the model structure and the set of the most influential regressors or lags. The main idea behind of the proposed method resembles to those techniques that prioritize lags evaluating the
2010 XXIX International Conference of the Chilean Computer Science Society, 2010
... presenting different conditions. The attributes extracted from a Poincaré plot are the stan-d... more ... presenting different conditions. The attributes extracted from a Poincaré plot are the stan-dard deviation of the projections of the data points onto the lines y = x and y = −x, SD1 and SD2, respectively [13]. Another measure computed ...
2008 Eighth International Conference on Hybrid Intelligent Systems, 2008
In this paper, we study a single objective extension of support vector machines for multicategory... more In this paper, we study a single objective extension of support vector machines for multicategory classification. Extending the dual formulation of binary SVMs, the algo-rithm looks for minimizing the sum of all the pairwise dis-tances among a set of prototypes, each one constrained to ...
Artificial neural networks (ANN) have been used as predictive systems for a variety of applicatio... more Artificial neural networks (ANN) have been used as predictive systems for a variety of application domains such as science, engineering and finance. Therefore it is very important to be able to estimate the reliability of a given model. Bootstrap is a computer intensive method used for estimating the distribution of a statistical estimator based on an imitation of the probabilistic
This paper proposes a new approach to train ensembles of learning machines in a regression contex... more This paper proposes a new approach to train ensembles of learning machines in a regression context. At each iteration a new learner is added to compensate the error made by the previous learner in the prediction of its training patterns. The algorithm operates directly over values to be predicted by the next machine to retain the ensemble in the target hypothesis and to ensure diversity. We expose a theoretical explanation which clarifies what the method is doing algorithmically and allows to show its stochastic convergence. Finally, experimental results are presented to compare the performance of this algorithm with boosting and bagging in two well-known data sets.
This paper describes the modelling of fuzzy rule systems using a multiresolution strategy that ha... more This paper describes the modelling of fuzzy rule systems using a multiresolution strategy that handles the problem of granularization of the input space by using multiresolution linguistic terms. Models of different resolutions are chained by antecedents because linguistic terms of a level j are obtained by refinements of linguistic terms of a superior level j + 1. The models can
Self-poised ensemble learning is based on the idea of introducing an artificial innovation to the... more Self-poised ensemble learning is based on the idea of introducing an artificial innovation to the map to be predicted by each machine in the ensemble such that it compensates the error incurred by the previous one. We will show that this approach is equivalent to regularize ...
A mathematical statistical model is needed to obtain an option prime and create a hedging strateg... more A mathematical statistical model is needed to obtain an option prime and create a hedging strategy. With formulas derived from stochastic differential equations, the primes for US Dollar/Chilean Pesos currency options using a prime calculator are obtained. Furthermore, a backward simulation of the option prime trajectory is used with a numerical method created for backward stochastic differential equations. The use
Communications in Statistics - Theory and Methods, 2004
In financial time series analysis, serial correlations and the volatility clustering effects of a... more In financial time series analysis, serial correlations and the volatility clustering effects of asset returns are commonly checked by Ljung-Box and Mcleod-Li Q test and filtered by ARMA models. However, it is known that the both tests are not robust to heavily tailed data. We ...
. Outliers in time series seriously affect conventional parameter estimates. In this paper a robu... more . Outliers in time series seriously affect conventional parameter estimates. In this paper a robust recursive estimation procedure for the parameters of auto‐regressve moving‐average models with additive outliers is proposed. Using ‘cleaned’ residuals from an initial robust fit of an autoregression of high order as input, bounded influence regression is applied recursively. The proposal follows certain ideas of Hannan and Rissanen, who suggested a three‐stage procedure for order and parameter estimation in a conventional setting.A Monte Carlo study is performed to investigate the robustness properties of the proposed class of estimates and to compare them with various other suggestions, including least squares, M estimates, residual autocovariance and truncated residual autocovariance estimates. The results show that the recursive generalized M estimates compare favourably with them. Finally, possible modifications to master even vigourous situations are suggested.
International Journal of Hybrid Intelligent Systems, 2009
Abstract. The margin maximization principle implemented by binary Support Vector Machines (SVMs) ... more Abstract. The margin maximization principle implemented by binary Support Vector Machines (SVMs) has been shown to be equivalent to find the hyperplane equidistant to the closest points belonging to the convex hulls that enclose each class of examples. In this paper, we ...
Abstract. We present a method for image segmentation, that is, to identify image points with an i... more Abstract. We present a method for image segmentation, that is, to identify image points with an indication of the region or class they belong to. The proposed algorithm basically consists of two stages. First it starts by restoring the image from possible contamination. In the ...
2012 IEEE 42nd International Symposium on Multiple-Valued Logic, 2012
In this work, a Takagi-Sugeno-Kang (TSK) model is used for time series analysis and some importan... more In this work, a Takagi-Sugeno-Kang (TSK) model is used for time series analysis and some important questions about the identification of this kind of models are addressed: the identification of the model structure and the set of the most influential regressors or lags. The main idea behind of the proposed method resembles to those techniques that prioritize lags evaluating the
2010 XXIX International Conference of the Chilean Computer Science Society, 2010
... presenting different conditions. The attributes extracted from a Poincaré plot are the stan-d... more ... presenting different conditions. The attributes extracted from a Poincaré plot are the stan-dard deviation of the projections of the data points onto the lines y = x and y = −x, SD1 and SD2, respectively [13]. Another measure computed ...
2008 Eighth International Conference on Hybrid Intelligent Systems, 2008
In this paper, we study a single objective extension of support vector machines for multicategory... more In this paper, we study a single objective extension of support vector machines for multicategory classification. Extending the dual formulation of binary SVMs, the algo-rithm looks for minimizing the sum of all the pairwise dis-tances among a set of prototypes, each one constrained to ...
Artificial neural networks (ANN) have been used as predictive systems for a variety of applicatio... more Artificial neural networks (ANN) have been used as predictive systems for a variety of application domains such as science, engineering and finance. Therefore it is very important to be able to estimate the reliability of a given model. Bootstrap is a computer intensive method used for estimating the distribution of a statistical estimator based on an imitation of the probabilistic
This paper proposes a new approach to train ensembles of learning machines in a regression contex... more This paper proposes a new approach to train ensembles of learning machines in a regression context. At each iteration a new learner is added to compensate the error made by the previous learner in the prediction of its training patterns. The algorithm operates directly over values to be predicted by the next machine to retain the ensemble in the target hypothesis and to ensure diversity. We expose a theoretical explanation which clarifies what the method is doing algorithmically and allows to show its stochastic convergence. Finally, experimental results are presented to compare the performance of this algorithm with boosting and bagging in two well-known data sets.
This paper describes the modelling of fuzzy rule systems using a multiresolution strategy that ha... more This paper describes the modelling of fuzzy rule systems using a multiresolution strategy that handles the problem of granularization of the input space by using multiresolution linguistic terms. Models of different resolutions are chained by antecedents because linguistic terms of a level j are obtained by refinements of linguistic terms of a superior level j + 1. The models can
Self-poised ensemble learning is based on the idea of introducing an artificial innovation to the... more Self-poised ensemble learning is based on the idea of introducing an artificial innovation to the map to be predicted by each machine in the ensemble such that it compensates the error incurred by the previous one. We will show that this approach is equivalent to regularize ...
A mathematical statistical model is needed to obtain an option prime and create a hedging strateg... more A mathematical statistical model is needed to obtain an option prime and create a hedging strategy. With formulas derived from stochastic differential equations, the primes for US Dollar/Chilean Pesos currency options using a prime calculator are obtained. Furthermore, a backward simulation of the option prime trajectory is used with a numerical method created for backward stochastic differential equations. The use
Communications in Statistics - Theory and Methods, 2004
In financial time series analysis, serial correlations and the volatility clustering effects of a... more In financial time series analysis, serial correlations and the volatility clustering effects of asset returns are commonly checked by Ljung-Box and Mcleod-Li Q test and filtered by ARMA models. However, it is known that the both tests are not robust to heavily tailed data. We ...
. Outliers in time series seriously affect conventional parameter estimates. In this paper a robu... more . Outliers in time series seriously affect conventional parameter estimates. In this paper a robust recursive estimation procedure for the parameters of auto‐regressve moving‐average models with additive outliers is proposed. Using ‘cleaned’ residuals from an initial robust fit of an autoregression of high order as input, bounded influence regression is applied recursively. The proposal follows certain ideas of Hannan and Rissanen, who suggested a three‐stage procedure for order and parameter estimation in a conventional setting.A Monte Carlo study is performed to investigate the robustness properties of the proposed class of estimates and to compare them with various other suggestions, including least squares, M estimates, residual autocovariance and truncated residual autocovariance estimates. The results show that the recursive generalized M estimates compare favourably with them. Finally, possible modifications to master even vigourous situations are suggested.
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Papers by Héctor Allende Olivares