Controlled capacity modeling tool

Details Controlled capacity modeling tool Controlled capacity modeling tool

2005-10-18

2005-10-18

Davis, George (Department: 2121)

Data processing: artificial intelligence

Neural network

Learning task

C706S023000

Reexamination Certificate

active

06957201

ABSTRACT:
A process for modeling numerical data for forecasting a phenomenon relates to constructing a model by processing and learning on collected data. The fit and robustness of the model are evaluated and the model parameters are adjusted to select an optimal model in the form of a Dthorder polynomial. A trade-off between learning accuracy and learning stability is controlled by adding to a covariance matrix a perturbation in the form of the product of a scalar λ times a matrix H or in the form of a matrix H dependent on a vector of k parameters Λ=(λ1, λ2, . . . λk). A data partition step can divide the data into a first subset for constructing the model and a second subset for adjusting the value of the model parameters according to a validity criterion obtained from data that was not used to construct the model.

REFERENCES:
patent: 5796922 (1998-08-01), Smith
patent: 6000833 (1999-12-01), Gershenfeld et al.
Rossius, R et al.“A short note about the application of polynomial kernels with fractional degree in support vector learning”,Machine Learning: ECML-98, 10thEuropean Conference on Machine Learning., Apr. 21, 1998, pp. 143-148, XP002115741.
Jonathan R. M. Hosking et al, “A statistical perspective on data mining”,Future Generation Computer Systems, 13 (1997), pp. 117-134.

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