Application of Lasso to the Eigenvector Selection Problem in Eigenvector Based Spatial Filtering

Application of eigenvector-based spatial filtering approach to a multinomial logit model for land use data

The present study builds a spatial statistical model for estimating land use maps. Many approaches for modeling land use maps exist in the literatures. A representative method includes a multinomial logit model (Miller and Plantinga, 1999), in which the likelihood of placing each land use category, such as land for building and forest, into each zone is explained by selected attributes such as ...

Features Selection via Eigenvector Centrality

In an era where accumulating data is easy and storing it inexpensive, feature selection plays a central role in helping to reduce the high-dimensionality of huge amounts of otherwise meaningless data. In this paper, we propose a graph-based method for feature selection that ranks features by identifying the most important ones into arbitrary set of cues. Mapping the problem on an affinity graph...

Spectral clustering with eigenvector selection

The task of discovering natural groupings of input patterns, or clustering, is an important aspect machine learning and pattern analysis. In this paper, we study the widely-used spectral clustering algorithm which clusters data using eigenvectors of a similarity/affinity matrix derived from a data set. In particular, we aim to solve two critical issues in spectral clustering: (1) How to automat...

Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging.

Diffuse optical imaging is an effective technique for noninvasive functional brain imaging. However, the measurements respond to systemic hemodynamic fluctuations caused by the cardiac cycle, respiration, and blood pressure, which may obscure or overwhelm the desired stimulus-evoked response. Previous work on this problem employed temporal filtering, estimation of systemic effects from backgrou...

Generalized Eigenvector Problem and Its Applications