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You searched for +publisher:"Université Catholique de Louvain" +contributor:("Cawley, Gavin C."). One record found.

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Université Catholique de Louvain

1. Delannay, Nicolas. Aspects of probabilistic modelling for data analysis.

Degree: 2007, Université Catholique de Louvain

Computer technologies have revolutionised the processing of information and the search for knowledge. With the ever increasing computational power, it is becoming possible to tackle new data analysis applications as diverse as mining the Internet resources, analysing drugs effects on the organism or assisting wardens with autonomous video detection techniques. Fundamentally, the principle of any data analysis task is to fit a model which encodes well the dependencies (or patterns) present in the data. However, the difficulty is precisely to define such proper model when data are noisy, dependencies are highly stochastic and there is no simple physical rule to represent them. The aim of this work is to discuss the principles, the advantages and weaknesses of the probabilistic modelling framework for data analysis. The main idea of the framework is to model dispersion of data as well as uncertainty about the model itself by probability distributions. Three data analysis tasks are presented and for each of them the discussion is based on experimental results from real datasets. The first task considers the problem of linear subspaces identification. We show how one can replace a Gaussian noise model by a Student-t noise to make the identification more robust to atypical samples and still keep the learning procedure simple. The second task is about regression applied more specifically to near-infrared spectroscopy datasets. We show how spectra should be pre-processed before entering the regression model. We then analyse the validity of the Bayesian model selection principle for this application (and in particular within the Gaussian Process formulation) and compare this principle to the resampling selection scheme. The final task considered is Collaborative Filtering which is related to applications such as recommendation for e-commerce and text mining. This task is illustrative of the way how intuitive considerations can guide the design of the model and the choice of the probability distributions appearing in it. We compare the intuitive approach with a simpler matrix factorisation approach.

(FSA 3) – UCL, 2007

Advisors/Committee Members: UCL - FSA/ELEC - Département d'électricité, Cawley, Gavin C., Absil, Pierre-Antoine, Vandendorpe, Luc, Saerens, Marco, Verleysen, Michel, Rossi, Fabrice.

Subjects/Keywords: Data mining; Machine learning; Bayesian statistics; Robust statistics; Regression; NIR spectroscopy; Collaborative filtering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Delannay, N. (2007). Aspects of probabilistic modelling for data analysis. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/5050

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Delannay, Nicolas. “Aspects of probabilistic modelling for data analysis.” 2007. Thesis, Université Catholique de Louvain. Accessed July 20, 2019. http://hdl.handle.net/2078.1/5050.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Delannay, Nicolas. “Aspects of probabilistic modelling for data analysis.” 2007. Web. 20 Jul 2019.

Vancouver:

Delannay N. Aspects of probabilistic modelling for data analysis. [Internet] [Thesis]. Université Catholique de Louvain; 2007. [cited 2019 Jul 20]. Available from: http://hdl.handle.net/2078.1/5050.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Delannay N. Aspects of probabilistic modelling for data analysis. [Thesis]. Université Catholique de Louvain; 2007. Available from: http://hdl.handle.net/2078.1/5050

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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