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Cloud Data Set

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Kristiaan Pelckmans and Jos De Brabanter and J. A. K Suykens and Bart De Moor and K. U. Leuven - ESAT. The Differogram: Non-parametric Noise Variance Estimation and its Use for Model Selection. SCDSISTA. 2004.

the tuning parameters of SVMs, see e.g. (Vapnik, 1998; Cherkassky and Ma, 2004). 6 Experiments Figure 1 and 2 show artificially generated data and the differogram cloud of a linear and nonlinear toy dataset respectively. The latter example was taken from (Wahba, 1990) using the function f(x) = 4.26(e -x -4e -2x +3e -3x ) such that y i = f(x i )+e i 21 for all i = 1, . . . , N . The random white noise


Stephen D. Bay. Nearest neighbor classification from multiple feature subsets. Intell. Data Anal, 3. 1999.

errors if different features were 17 selected. With this method they were able to improve performance on 7 of 10 domains tested (7 from the UCI repository and 3 proprietary cloud classification datasets), and they noted that ECOC accuracy gains tended to increase with increased diversity among the features selected for the two-class problems. NN-ECOC is similar to MFS as they both use NN


C. esar and Cesar Guerra-Salcedo and Darrell Whitley. Feature Selection Mechanisms for Ensemble Creation : A Genetic Search Perspective. Department of Computer Science Colorado State University.

Features Classes Train Size Test Size LandSat 36 6 4435 2000 DNA 180 39 2000 1186 Segment 19 7 210 2100 Cloud 204 10 1000 633 Table 1: Dataset employed for the experiments. In the DNA dataset the attributes values are 0 or 1. In the Segment and the Cloud dataset the attributes values are floats. In the LandSat dataset the attribute values


Cesar Guerra-Salcedo and Stephen Chen and Darrell Whitley and Sarah Smith. Fast and Accurate Feature Selection Using Hybrid Genetic Strategies. Department of Computer Science Colorado State University.

(LandSat), a DNA classification dataset and a Cloud classification dataset. On the other hand, the artificially generated classification problem rely on a LED identification problem. LED cases are artificially generated using a test case


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