Visualization of High-Dimensional Data Using Two-Dimensional Self-Organizing Piecewise-Smooth Kohonen Maps

A. V. Shklovets; N. G. Axak

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Visualization of High-Dimensional Data Using Two-Dimensional Self-Organizing Piecewise-Smooth Kohonen Maps

机译：使用二维自组织分段平滑Kohonen映射可视化高维数据

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摘要

To make visualization of high-dimensional data more accurate, we offer a method of approximating two-dimensional Kohonen maps lying in a multiple-dimensional space. Cubic parametric spline-based least-defect surfaces can be used as an approximation function to minimize approximation errors.

机译：为了使高维数据的可视化更加准确，我们提供了一种近似位于多维空间中的二维Kohonen映射的方法。三次参数基于样条曲线的最小缺陷曲面可用作近似函数，以使近似误差最小化。

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来源
《Optical memory & neural networks》 |2012年第4期|227-232|共6页
作者
A. V. Shklovets; N. G. Axak;
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作者单位

Kharkov National Radioelectronics University, Ukraine;

Kharkov National Radioelectronics University, Ukraine;

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原文格式 PDF
正文语种 eng
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关键词
visualization of high-dimensional data; two-dimensional piecewise-smooth kohonen maps; parametric spline-based surface;

机译：可视化高维数据;二维分段平滑的kohonen图;基于参数样条的曲面;

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2. Self-Organizing Map and Relational Perspective Mapping for the Accurate Visualization of High-Dimensional Hyperspectral Data [J] . Gardner Wil, Maliki Ruqaya, Cutts Suzanne M., Analytical chemistry . 2020,第15期

机译：自组织地图和关系透视映射，用于高维光谱数据的准确可视化
3. Using self-organizing maps to visualize high-dimensional data [J] . Penn BS Computers & geosciences . 2005,第5期

机译：使用自组织地图可视化高维数据
4. Visualizing High-Dimensional Input Data with Growing Self-Organizing Maps [C] . Soledad Delgado, Consuelo Gonzalo, Estibaliz Martinez, International Work-Conference on Artificial Neural Networks(IWANN 2007); 20070620-22; San Sebastian(ES) . 2007

机译：使用不断增长的自组织映射图可视化高维输入数据
5. A software environment for visualizing high-dimensional data using contextual self-organizing maps linked with immersive virtual reality [D] . Richardson, Trevor Thomas 2013

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6. Metabolite-based clustering and visualization of mass spectrometry data using one-dimensional self-organizing maps [O] . Peter Meinicke, Thomas Lingner, Alexander Kaever, 2008

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7. Self-Organizing Map and Relational Perspective Mapping for the Accurate Visualization of High-Dimensional Hyperspectral Data [O] . -1

机译：自组织地图和关系透视映射，以准确可视化高维光谱数据

Visualization of High-Dimensional Data Using Two-Dimensional Self-Organizing Piecewise-Smooth Kohonen Maps

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