In this work we propose a hierarchical clustering methodology for hyperspectral data based on the Hotelling’s T 2 statistic. For each hypespectral sample data, the statistical sample mean is calculated using a window-based neighborhood. Then, the pairwise similarities between any two hyperspectral samples are computed in base to the Hotelling’s T 2 statistic. This statistic assumes a Gaussian d...

The problem of hierarchical clustering items from pairwise similarities is found across various scientific disciplines, from biology to networking. Often, applications of clustering techniques are limited by the cost of obtaining similarities between pairs of items. While prior work has been developed to reconstruct clustering using a significantly reduced set of pairwise similarities via adapt...

Our paper is concerned with investigating the impact of translationese on the novels of a bilingual writer and asking whether one could determine the authorship of a translated document. The main part of our paper will be centered on selecting a good set of lexical features that can be considered characteristic for an author. We used in our research the novels of Vladimir Nabokov, a bilingual a...

To realize privacy data protection efficiently in hybrid cloud service, a hierarchical control architecture based multi-cluster MapReduce programming model (the Hierarchical MapReduce Model, HMR) is presented. Under this hierarchical control architecture, data isolation and placement among private cloud and public clouds according to the data privacy characteristic is implemented by the control...

this paper presents results of hydro-chemical processes controlling groundwater chemical composition, using an integrated application of hierarchical cluster analysis and factor analysis of a major ion data set of groundwater from mighan playa aquifer. cluster analysis classified samples into four clusters(a, b, c and d) according to their dominant chemical composition: cluster a (dominant comp...

I review the main steps made so far towards a detailed (semi) analytical model for the hierarchical clustering of bound virialized objects (i.e., haloes) in the gravitational instability scenario. I focus on those models relying on the spherical collapse approximation which have led to the most complete description. The work is divided in two parts: a first one dealing with the mass function of...

This work analyzes the distribution of past CS229 projects by applying hierarchical agglomerative clustering. The clusters reveal which topics are very popular and which topics are more unique. Tracking the clusters over time also provides insight into how student projects have shifted over time. This knowledge will help future students select interesting and unique projects.

We describe the Hierarchical Classifier (HC), which is a hybrid architecture [1] built with the help of supervised training and unsu-pervised problem clustering. We prove a theorem giving the estimationˆR of HC risk. The proof works because of an improved way of computing cluster weights, introduced in this paper. Experiments show thatˆR is correlated with HC real error. This allows us to usê R...