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Unfolding preprocessing for meaningful time series clustering

• Geoffroy Simon, John Aldo Lee, Michel Verleysen
• Neural Networks
• 2006

Clustering methods are commonly applied to time series, either as a preprocessing stage for other methods or in their own right. In this paper it is explained why time series clustering may sometimes… (More)

On the Effects of Dimensionality on Data Analysis with Neural Networks

• Michel Verleysen, Damien François, Geoffroy Simon, Vincent Wertz
• IWANN
• 2003

Modern data analysis often faces high-dimensional data. Nevertheless, most neural network data analysis tools are not adapted to highdimensional spaces, because of the use of conventional concepts… (More)

Fast bootstrap for least-square support vector machines

• Amaury Lendasse, Geoffroy Simon, Vincent Wertz, Michel Verleysen
• ESANN
• 2004

The Bootstrap resampling method may be efficiently used to estimate the generalization error of nonlinear regression models, as artificial neural networks and especially Least-square Support Vector… (More)

Double quantization of the regressor space for long-term time series prediction: method and proof of stability

• Geoffroy Simon, Amaury Lendasse, Marie Cottrell, Jean-Claude Fort, Michel Verleysen
• Neural Networks
• 2004

The Kohonen self-organization map is usually considered as a classification or clustering tool, with only a few applications in time series prediction. In this paper, a particular time series… (More)

Double SOM for long-term time series prediction

• Geoffroy Simon, Amaury Lendasse, Marie Cottrell, Jean-Claude Fort, Michel Verleysen
• 2003

-Many time series forecasting problems require the estimation of possibly inaccurate, but longterm, trends, rather than accurate short-term prediction. In this paper, a double use of the… (More)

Time series forecasting: Obtaining long term trends with self-organizing maps

• Geoffroy Simon, Amaury Lendasse, Marie Cottrell, Jean-Claude Fort, Michel Verleysen
• Pattern Recognition Letters
• 2005

Kohonen self-organisation maps are a well know classification tool, commonly used in a wide variety of problems, but with limited applications in time series forecasting context. In this paper, we… (More)

Time series forecasting with SOM and local non-linear models - Application to the DAX30 index prediction

• Simon Dablemont, Geoffroy Simon, Amaury Lendasse, A. Ruttiens, François Blayo, Michel Verleysen
• 2003

A general method for time series forecasting is presented. Based on the splitting of the past dynamics into clusters, local models are built to capture the possible evolution of the series given the… (More)

Forecasting the CATS benchmark with the Double Vector Quantization method

• Geoffroy Simon, John Aldo Lee, Marie Cottrell, Michel Verleysen
• Neurocomputing
• 2007

The Double Vector Quantization method, a long-term forecasting method based on the SOM algorithm, has been used to predict the 100 missing values of the CATS competition data set. An analysis of the… (More)

High-dimensional delay selection for regression models with mutual information and distance-to-diagonal criteria

• Geoffroy Simon, Michel Verleysen
• Neurocomputing
• 2007

Delay selection for time series phase space reconstruction may be performed using a mutual information (MI) criterion. However, the delay selection is in that case limited to the estimation of a… (More)

On the need of unfolding preprocessing for time series clustering

• Geoffroy Simon, John A. Lee, Michel Verleysen
• 2005

Clustering methods are commonly used on time series, either as a preprocessing for other methods or for themselves. This paper illustrates the problem of clustering applied on regressor vectors… (More)

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