Data Visualization With Multidimensional Scaling
نویسندگان
چکیده
منابع مشابه
Data Visualization With Multidimensional Scaling
We discuss methodology for multidimensional scaling (MDS) and its implementation in two software systems, GGvis and XGvis. MDS is a visualization technique for proximity data, that is, data in the form of N × N dissimilarity matrices. MDS constructs maps (“configurations,” “embeddings”) in IRk by interpreting the dissimilarities as distances. Two frequent sources of dissimilarities are high-dim...
متن کاملXGvis: Interactive Data Visualization with Multidimensional Scaling
We discuss interactive techniques for multidimensional scaling (MDS) and a system, named \XGvis", that implements these techniques. MDS is a method for visualizing proximity data, that is, data where objects are characterized by dissimilarity values for all pairs of objects. MDS constructs maps of these objects in IR k by interpreting the dissimilarities as distances. MDS in its conventional ba...
متن کاملVisualization Methodology for Multidimensional Scaling
We describe methodology for multidimensional scaling based on interactive data visualization. This methodology was enabled by software in which MDS is integrated in a multivariate data visualization system. The software, called “XGvis”, is described in a companion paper (Buja, Swayne, Littman, Dean and Hofmann 2001), that lays out the implemented functionality in some detail; in the current pap...
متن کاملData visualization by multidimensional scaling: a deterministic annealing approach
Multidimensional scaling addresses the problem how proximity data can be faithfully visualized as points in a low-dimensional Euclidean space. The quality of a data embedding is measured by a stress function which compares proximity values with Euclidean distances of the respective points. The corresponding minimization problem is non-convex and sensitive to local minima. We present a novel det...
متن کاملHigh Performance Multidimensional Scaling for Large High-Dimensional Data Visualization
Technical advancements produces a huge amount of scientific data which are usually in high dimensional formats, and it is getting more important to analyze those large-scale high-dimensional data. Dimension reduction is a well-known approach for high-dimensional data visualization, but can be very time and memory demanding for large problems. Among many dimension reduction methods, multidimensi...
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: Journal of Computational and Graphical Statistics
سال: 2008
ISSN: 1061-8600,1537-2715
DOI: 10.1198/106186008x318440