Support Vector Method for Multivariate Density Estimation
نویسندگان
چکیده
Sayan Mukherjee CBCL, MIT E25-201 Cambridge, MA 02142 [email protected] A new method for multivariate density estimation is developed based on the Support Vector Method (SVM) solution of inverse ill-posed problems. The solution has the form of a mixture of densities. This method with Gaussian kernels compared favorably to both Parzen's method and the Gaussian Mixture Model method. For synthetic data we achieve more accurate estimates for densities of 2, 6, 12, and 40 dimensions.
منابع مشابه
Multivariate Density Estimation: a Support Vector Machine Approach
A Support Vector Machine (SVM) algorithm for multivariate density estimation is developed based on regularization principles and bounds on the convergence of empirical distribution functions. The algorithm is compared to Gaussian Mixture Models (GMMs). Our algorithm outperforms GMMs for data drawn from mixtures of gaussians in IR 2 and IR 6. Our algorithm is also automated with respect to param...
متن کاملPermeability estimation from the joint use of stoneley wave velocity and support vector machine neural networks: a case study of the Cheshmeh Khush Field, South Iran
Accurate permeability estimation has always been a concern in determining flow units, assigning appropriate capillary pressure andrelative permeability curves to reservoir rock types, geological modeling, and dynamic simulation.Acoustic method can be used as analternative and effective tool for permeability determination. In this study, a four-step approach is proposed for permeability estimati...
متن کاملA new classification method based on pairwise SVM for facial age estimation
This paper presents a practical algorithm for facial age estimation from frontal face image. Facial age estimation generally comprises two key steps including age image representation and age estimation. The anthropometric model used in this study includes computation of eighteen craniofacial ratios and a new accurate skin wrinkles analysis in the first step and a pairwise binary support vector...
متن کاملApplication of Artificial Neural Networks and Support Vector Machines for carbonate pores size estimation from 3D seismic data
This paper proposes a method for the prediction of pore size values in hydrocarbon reservoirs using 3D seismic data. To this end, an actual carbonate oil field in the south-western part ofIranwas selected. Taking real geological conditions into account, different models of reservoir were constructed for a range of viable pore size values. Seismic surveying was performed next on these models. F...
متن کاملEstimation of Iron concentration by using a support vector machineand an artificial neural network - the case study of the Choghart deposit southeast of Yazd, Yazd, Iran
Estimation of the metal value in the metallic deposits is one of the important factors to evaluate the deposits in exploration studies andmineral processing. Therefore, one accurate estimator is essential to obtain a fine insight into the accumulation of the ore body. Thereare geostatistical methods for the estimation of the concentration of iron which performance of these models is complexity ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1999