Recently, the the support vector machine (SVM) has become a popular tool in time series forecasting. In developing a successful SVM forecaster, the first step is feature extraction. This paper proposes the applications of principal component analysis (PCA), kernel principal component analysis (KPCA) and independent component analysis (ICA) to SVM for feature extraction. The PCA linearly transforms the original inputs into new uncorrelated features. The KPCA is a nonlinear PCA developed by using the kernel method. In ICA, the original inputs are linearly transformed into features which are mutually statistically independent. By examining the sunspot data, Santa Fe data set A and five real futures contracts, the experiment shows that SVM by feature extraction using PCA, KPCA or ICA can pe...
... is in the truest sense of the word the kernel where everyday solidarity is practiced. .. Even if...
Risk assessment of credit portfolios is of pivotal importance in the banking industry. The bank that has the most accurate view of its credit risk will be the most profitable. One of the main pillars in the assessing credit risk is the estimated probability of default of each counterparty, i.e., the probability that a counterparty cannot meet its payment obligations in the horizon of one year. A credit rating system takes several characteristics of a counterparty as inputs and assigns this counterparty to a rating class. In essence, this system is a classifier whose classes lie on an ordinal scale. In this paper we apply linear regression ordinal logistic regression, and support vector machine techniques to the credit rating problem. The latter technique is a relatively new machine lear...
... provide any details on the choice of the kernel function and the hyperparameter selection method. ...
This teaching case study focuses on the shifting of company strategy from the national to the CEE-regional level. Friesland, a Dutch-owned dairy company in Hungary, was extremely successful in the national context since 1993, but the 2004-enlargement of the European Union initiated a process of regional integration across Central European countries. Management has to face new challenges for company strategy (such as regional expansion) and organisational structures (fitting an existing national company to the new international group of businesses).
...Suddenly it seemed to Kernel that at least the traffic jam got dissolved, but h...
Several popular Machine Learning techniques are originally designed for the solution of two-class problems. However, several classification problems have more than two classes. One approach to deal with multiclass problems using binary classifiers is to decompose the multiclass problem into multiple binary sub-problems disposed in a binary tree. This approach requires a binary partition of the classes for each node of the tree, which defines the tree structure. This paper presents two algorithms to determine the tree structure taking into account information collected from the used dataset. This approach allows the tree structure to be determined automatically for any multiclass dataset.
...Cheong et al. [15] employed a Kernel-based SOM Neural Network (KSOM) for the conversion...
In this paper, we propose a method to predict wind power production with radial basis function networks. In this case, the power production is the aggregated production of all wind farms of one electricity company. The method uses wind speed predictions supplied by a meteorological agency, and predicts up to several days ahead. The coarse resolution of one meter per second is overcome by combining the weather data from several meteorological stations. The wind direction is mapped on a circle, so it is more compatible with a radial basis. These ingredients have been combined with a kernel machine, which has been implemented and tested. Test results are presented in the paper.
Forecasting arrival times of a vehicle at many downstream stops is very important in many cases. For multi-stop arrival time prediction, direct approaches and iterative approaches possess respective merits. Therefore, a hybrid method that has both direct and iterative modeling abilities is presented to forecast arrival times at multiple stops. The hybrid method consists of an iterative support vector machine (SVM)-based prediction model and a direct SVM-based prediction model. In hybrid model, output from the iterative model is a rough prediction and it also needs to be adjusted, based on output from the direct model. The proposed model is assessed with the data of transit route number 3 in Guiyang city, China. Results show that the hybrid model seems to be a powerful tool for multi-sto...
...By introducing kernel function K(x^sub i^,x^sub j^) the Eq.(5) can be re...
A common approach in the multiple criteria decision making is to obtain the overall evaluation by aggregating the partial evaluations. For this, a member of a large family of aggregation operators is used. Many of these operators commonly employed in decision making (weighted average, ordered weighted average, minimum, maximum, . . .) can be used only when criteria are independent. On the other hand, the Choquet integral, a generalization of the aforementioned operators, can be used even when some interactions between criteria occur. We present a fuzzified Choquet integral capable of dealing not only with fuzzy partial evaluations (first level fuzzification), but also with fuzzy weights (second level fuzzification). We also provide an effective way to evaluate the fully fuzzified integr...
... numbers IR with following properties: The kernel of C. Ker C = {x ∈ R | C(x) = 1} is nonempty, th...
With the purpose of guaranteeing the copyright and security of software, we introduce the structural fingerprint and the distance of the fingerprint to find the same source programs from a great deal of programs in this paper. In order to gain the structural fingerprint, the in-degree, out-degree and adjacency relationship are exacted from call graph to construct a structural matrix. Then this matrix is mapped to RGB image and to compute the color moments of this image. Comparing with the traditional binary comparison way in which finding graph isomorphism is based on control flow graph or instruction similarity, this method offers many advantages in application. First of all, the image processing techniques are made full use of to gain the color moments that are considered as the struc...
... mapping function corresponding to Mercer kernel x. This dual problem can be solved by Quadratic Pr...
German unification merged two contrasting family models: the East German dual-worker model and the West German male breadwinner model. Since 2002, Germany has been essentially changing directions towards a third model called "sustainable family policy." The new policy model conceives of children as society's future assets, seeks to encourage childbearing by supporting parents to be workers and attempts to reduce families' poverty by boosting mothers' employment. By increasing childcare facilities also of very small children and by developing early childhood education politicians claim to invest in children, make up for social inequalities and generate "sustainable. human capital. The ongoing family policy change seems at odds with mainstream judgments on reform incapability of the Germa...
... is in the truest sense of the word the kernel where everyday solidarity is practiced. .. Even if...
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