The paper discusses the significance of cultural capital for the understanding of the field of housing in contemporary Britain. It explores the relationship between housing and the position of individuals in social space mapped out by means of a multiple correspondence analysis. It considers the material aspects of housing and the changing contexts that are linked to the creation and display of...

Correspondence analysis has found extensive use in ecology, archaeology, linguistics, and the social sciences as a method for visualizing the patterns of association in a table of frequencies or nonnegative ratio-scale data. Inherent to the method is the expression of the data in each row or each column relative to their respective totals, and it is these sets of relative values (called profile...

A common problem for clustering techniques is that clusters overlap, which makes graphing the statistical structure in the data difficult. A related problem is that we often want to see the distribution of factors (variables) as well as classes (objects). Correspondence Analysis (CA) offers a solution to both these problems. The structure that CA discovers may be an important step in representi...

Several effective methods for improving the performance of a single learning algorithm have been developed recently. The general approach is to create a set of learned models by repeatedly applying the algorithm to different versions of the training data, and then combine the learned models' predictions according to a prescribed voting scheme. Little work has been done in combining the predicti...

Agglomerative clustering, Two Way Indicator Species Analysis (WINSPAN), and Detrended Correspondence Analysis (DCA) were used for the plant community analysis. Remotely sensed data was used as a surrogate in identifying and locating field sites from where floristic composition, environmental and spatial data were collected. Characteristic plant species of each community type are presented toget...