Adaptive and Natural Computing Algorithms: 10th - download pdf or read online
By Ivan Bratko (auth.), Andrej Dobnikar, Uroš Lotrič, Branko à ter (eds.)
The two-volume set LNCS 6593 and 6594 constitutes the refereed lawsuits of the tenth foreign convention on Adaptive and traditional Computing Algorithms, ICANNGA 2010, held in Ljubljana, Slovenia, in April 2010. The eighty three revised complete papers offered have been conscientiously reviewed and chosen from a complete of a hundred and forty four submissions. the 1st quantity comprises forty two papers and a plenary lecture and is equipped in topical sections on neural networks and evolutionary computation.
Read Online or Download Adaptive and Natural Computing Algorithms: 10th International Conference, ICANNGA 2011, Ljubljana, Slovenia, April 14-16, 2011, Proceedings, Part I PDF
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Extra resources for Adaptive and Natural Computing Algorithms: 10th International Conference, ICANNGA 2011, Ljubljana, Slovenia, April 14-16, 2011, Proceedings, Part I
Dobnikar, U. Lotrič, and B. ): ICANNGA 2011, Part I, LNCS 6593, pp. 41–50, 2011. © Springer-Verlag Berlin Heidelberg 2011 42 S. Osowski and K. Siwek 2 The Theoretical Basis of Integration of Predictors Prediction of the time series means to predict the present value x(n) or set of such values given past values of this process and other external signals influencing the process. The prediction task may be viewed as a form of model building in the sense that the smaller we make the prediction error in a statistical sense the better the network serves as a model of the underlying physical process responsible for generating the data.
L2μ ) is continuous; ∗ (ii) LK = JK : (L2μ (X), . L2μ ) → (HK (X), . K ) and so LK is continuous; (iii) TK is a Hilbert-Schmidt operator and both JK and LK are compact. To describe a relationship between RKHSs induced by two diﬀerent scalings, K a and K b , of the same kernel K we apply the spectral theorm to the operator TK := JK LK obtained by composing LK with JK . The next theorem from  summarizes some properties of eigenfunctions and eigenvalues of these operators. Theorem 3. Let X ⊆ Rd be measurable, μ a σ-finite measure on X, K : X × X → R symmetric positive semidefinite with X K(x, x)dμ(x) < ∞.
Similarly, if a reliability estimator does not outperform the reference reliability, it is not considered to be useful. We consider four additional estimators of single prediction reliability in the following. When measuring the distance between two probability distributions, the Hellinger distance was used. 1 Local Modeling of Prediction Error Let K be the predictor’s class probability distribution for a given unlabeled example (x, ). This approach to local estimation of prediction reliability is based on the nearest neighbors’ labels.
Adaptive and Natural Computing Algorithms: 10th International Conference, ICANNGA 2011, Ljubljana, Slovenia, April 14-16, 2011, Proceedings, Part I by Ivan Bratko (auth.), Andrej Dobnikar, Uroš Lotrič, Branko à ter (eds.)