Eigen-analysis of nonlinear PCA with polynomial kernels
نویسندگان
چکیده
منابع مشابه
Eigen-analysis of nonlinear PCA with polynomial kernels
There has been growing interest in kernel methods for classification, clustering and dimension reduction. For example, kernel Fisher discriminant analysis, spectral clustering and kernel principal component analysis are widely used in statistical learning and data mining applications. The empirical success of the kernel method is generally attributed to nonlinear feature mapping induced by the ...
متن کاملAnalysis of convergence of solution of general fuzzy integral equation with nonlinear fuzzy kernels
Fuzzy integral equations have a major role in the mathematics and applications.In this paper, general fuzzy integral equations with nonlinear fuzzykernels are introduced. The existence and uniqueness of their solutions areapproved and an upper bound for them are determined. Finally an algorithmis drawn to show theorems better.
متن کاملLearning with Cross-Kernels and Ideal PCA
We describe how cross-kernel matrices, that is, kernel matrices between the data and a custom chosen set of ‘feature spanning points’ can be used for learning. The main potential of cross-kernels lies in the fact that (a) only one side of the matrix scales with the number of data points, and (b) cross-kernels, as opposed to the usual kernel matrices, can be used to certify for the data manifold...
متن کاملIncremental online PCA for automatic motion learning of eigen behaviour
This paper presents an online learning framework for the behavior of an articulated body by capturing its motion using real-time video. In our proposed framework, supervised learning is first utilised during an offline learning phase for small instances using principal component analysis (PCA); then we apply a new incremental PCA technique during an online learning phase. Rather than storing al...
متن کاملFast LIC with Piecewise Polynomial Filter Kernels
Line integral convolution (LIC) has become a well-known and popular method for visualizing vector elds. The method works by convolving a random input texture along the integral curves of the vector eld. In order to accelerate image synthesis signiicantly, an eecient algorithm has been proposed that utilizes pixel coherence in eld line direction. This algorithm, called \fast LIC", originally was...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistical Analysis and Data Mining: The ASA Data Science Journal
سال: 2013
ISSN: 1932-1864
DOI: 10.1002/sam.11211