Showing 1 - 10 of 710
To minimize the primal support vector machine (SVM) problem, we propose to use iterative majorization. To do so, we propose to use it- erative majorization. To allow for nonlinearity of the predictors, we use (non)monotone spline transformations. An advantage over the usual ker- nel approach in...
Persistent link: https://www.econbiz.de/10005450850
Support vector machines (SVM) are becoming increasingly popular for the prediction of a binary dependent variable. SVMs perform very well with respect to competing techniques. Often, the solution of an SVM is obtained by switching to the dual. In this paper, we stick to the primal support vector...
Persistent link: https://www.econbiz.de/10005450870
Consider the classification task of assigning a test object to one of two or more possible groups, or classes. An intuitive way to proceed is to assign the object to that class, to which the distance is minimal. As a distance measure to a class, we propose here to use the distance to the convex...
Persistent link: https://www.econbiz.de/10005450881
We propose to estimate the parameters of the Market Share Attraction Model (Cooper & Nakanishi, 1988; Fok & Franses, 2004) in a novel way by using a non-parametric technique for function estimation called Support Vector Regressions (SVR) (Vapnik, 1995; Smola, 1996). Traditionally, the parameters of the...
Persistent link: https://www.econbiz.de/10004991089
Several instance-based large-margin classi¯ers have recently been put forward in the literature: Support Hyperplanes, Nearest Convex Hull classifier, and Soft Nearest Neighbor. We examine those techniques from a common fit-versus-complexity framework and study the links be- tween them....
Persistent link: https://www.econbiz.de/10004991123
A new classification method is proposed, called Support Hy- perplanes (SHs). To solve the binary classification task, SHs consider the set of all hyperplanes that do not make classification mistakes, referred to as semi-consistent hyperplanes. A test object is classified using that...
Persistent link: https://www.econbiz.de/10004991143
Classical multivariate analysis techniques such as principal components analysis and correspondence analysis use inner products to estimate data values. The results of these techniques may be visualized by representing the row and column points jointly in a biplot where the projection of a row...
Persistent link: https://www.econbiz.de/10005505007
Most recommender systems present recommended products in lists to the user. By doing so, much information is lost about the mutual similarity between recommended products. We propose to represent the mutual similarities of the recommended products in a two dimensional space, where similar...
Persistent link: https://www.econbiz.de/10005450836
This paper is concerned with time series forecasting in the presence of a large number of predictors. The results are of interest, for instance, in macroeconomic and financial forecasting where often many potential predictor variables are available. Most of the current forecast methods with many...
Persistent link: https://www.econbiz.de/10005450877
In this paper, we propose a new model that combines the vector model and the ideal point model of unfolding. An algorithm is developed, called VIPSCAL, that minimizes the combined loss both for ordinal and interval transformations. As such, mixed representations including both vectors and ideal...
Persistent link: https://www.econbiz.de/10005450890