Multidimensional Data Projection Algorithms Saving Calculations of Distances

نویسندگان

  • Rasa Karbauskaitė
  • Gintautas Dzemyda
چکیده

Abstract. In this paper, the triangulation method, the classic algorithm for Sammon’s projection and the combination of Sammon’s algorithm with the triangulation method are examined for mapping new points in detail. A new realization of the combination of Sammon’s algorithm and the triangulation method is proposed. These algorithms are analyzed and compared in the following respects: visual evaluation of data projection, evaluation of data mapping time and evaluation of projection error.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Multigrid multidimensional scaling

Multidimensional scaling (MDS) is a generic name for a family of algorithms that construct a configuration of points in a target metric space from information about inter-point distances measured in some other metric space. Large-scale MDS problems often occur in data analysis, representation and visualization. Solving such problems efficiently is of key importance in many applications. In this...

متن کامل

U-maps: topograpic visualization techniques for projections of high dimensional data

The visualization of distance structures in high dimensional data as topographic maps (U-matrix) is a standard method for Emergent Self Organizing Maps (ESOM). This work describes the extension of this visualization to other projections like principal component analysis (PCA), independent component analysis (ICA), multidimensional scaling (MDS), Sammon’s mapping, or Isomap. Each of the methods ...

متن کامل

A Family of Selective Partial Update Affine Projection Adaptive Filtering Algorithms

In this paper we present a general formalism for the establishment of the family of selective partial update affine projection algorithms (SPU-APA). The SPU-APA, the SPU regularized APA (SPU-R-APA), the SPU partial rank algorithm (SPU-PRA), the SPU binormalized data reusing least mean squares (SPU-BNDR-LMS), and the SPU normalized LMS with orthogonal correction factors (SPU-NLMS-OCF) algorithms...

متن کامل

A geometric view of Biodiversity: scaling to metagenomics

We have designed a new efficient dimensionality reduction algorithm in order to investigate new ways of accurately characterizing the biodiversity, namely from a geometric point of view, scaling with large environmental sets produced by NGS (∼ 10 sequences). The approach is based on Multidimensional Scaling (MDS) that allows for mapping items on a set of n points into a low dimensional euclidea...

متن کامل

ProxiViz: an Interactive Visualization Technique to Overcome Multidimensional Scaling Artifacts

Projection algorithms such as multidimensional scaling are often used to visualize high-dimensional data. However, when attempting to interpret the visualization of the resulting 2D projection, users are faced with artifacts. This poster introduces ProxiViz: an interactive technique to provide better insights about the original data-space. Primary results of a controlled experiment show that Pr...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2006