نتایج جستجو برای: variably scaled radial kernel
تعداد نتایج: 133573 فیلتر نتایج به سال:
We explore some of the convergence and generalization properties of the Bayes Point Machine (BPM) developed by Herbrich [3], an alternative to the Support Vector Machine (SVM) for classi cation. In the separable case, there are an in nite number of hyperplanes in version space that will perfectly separate the data. Instead of choosing a solution based on maximizing the margin (as with the SVM),...
The purpose of this study is to classify EEG data on imagined speech in a single trial. We recorded EEG data while five subjects imagined different vowels, /a/, /e/, /i/, /o/, and /u/. We divided each single trial dataset into thirty segments and extracted features (mean, variance, standard deviation, and skewness) from all segments. To reduce the dimension of the feature vector, we applied a f...
KLEPÁČ VÁCLAV, HAMPEL DAVID. 2016. Prediction of Bankruptcy with SVM Classifi ers Among Retail Business Companies in EU. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 64(2): 627–634. Article focuses on the prediction of bankruptcy of the 850 medium-sized retail business companies in EU from which 48 companies gone bankrupt in 2014 with respect to lag of the used featur...
We consider kernel-based learning methods for regression and analyze what happens to the risk minimizer when new variables, statistically independent of input and target variables, are added to the set of input variables. This problem arises, for example, in the detection of causality relations between two time series. We find that the risk minimizer remains unchanged if we constrain the risk m...
The theories for radial basis functions (RBFs) as well as piecewise polynomial splines have reached a stage of relative maturity as is demonstrated by the recent publication of a number of monographs in either field. However, there remain a number of issues that deserve to be investigated further. For instance, it is well known that both splines and radial basis functions yield “optimal” interp...
A structural similarity kernel is presented in this paper for SVM learning, especially for learning with imbalanced datasets. Kernels in SVM are usually pairwise, comparing the similarity of two examples only using their feature vectors. By building a neighborhood graph (kNN graph) using the training examples, we propose to utilize the similarity of linking structures of two nodes as an additio...
Compared to linear kernel, nonlinear kernels can often substantially improve the accuracies of many machine learning algorithms. In this paper, we compare 5 different nonlinear kernels: minmax, RBF, fRBF (folded RBF), acos, and acos-χ, on a wide range of publicly available datasets. The proposed fRBF kernel performs very similarly to the RBF kernel. Both RBF and fRBF kernels require an importan...
We address the problem of estimating human body pose from a single image with cluttered background. We train multiple local linear regressors for estimating the 3D pose from a feature vector of gradient orientation histograms. Each linear regressor is capable of selecting relevant components of the feature vector depending on pose by training it on a pose cluster which is a subset of the traini...
We derive new bounds on covering numbers for hypothesis classes generated by convex combinations of basis functions. These are useful in bounding the generalization performance of algorithms such as RBF-networks, boosting and a new class of linear programming machines similar to SV machines. We show that p-convex combinations with p > 1 lead to diverging bounds, whereas for p = 1 good bounds in...
Introduction: In the lung cancers, a computer-aided detection system that is capable of detecting very small glands in high volume of CT images is very useful.This study provided a novelsystem for detection of pulmonary nodules in CT image. Methods: In a case-control study, CT scans of the chest of 20 patients referred to Yazd Social Security Hospital were examined. In the two-dimensional and ...
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