Guided Projections for Analyzing the Structure of High-Dimensional Data-Reference-Cited by-同舟云学术

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Guided Projections for Analyzing the Structure of High-Dimensional Data

Published:2018-10-02 Issue:4 Volume:27 Page:750-762
ISSN:1061-8600
Container-title:Journal of Computational and Graphical Statistics
language:en
Short-container-title:Journal of Computational and Graphical Statistics

Author:

Ortner Thomas¹,Filzmoser Peter¹,Rohm Maia²,Breiteneder Christian²,Brodinova Sarka²

Affiliation:

1. Institute of Statistics and Mathematical Methods in Economics, Vienna University of Technology, Vienna, Austria

2. Institute of Software Technology and Interactive Systems, Vienna University of Technology, Vienna, Austria

Funder

Vienna Science and Technology Fund

österreichische Forschungsförderungsgesellschaft

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Discrete Mathematics and Combinatorics,Statistics and Probability

Link

http://www.tandfonline.com/doi/pdf/10.1080/10618600.2018.1459304

Reference33 articles.

1. Database-friendly random projections: Johnson-Lindenstrauss with binary coins

2. An Introduction to Kernel and Nearest-Neighbor Nonparametric Regression

3. Measuring the Power of Hierarchical Cluster Analysis

4. Diffusion maps

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Local projections for high-dimensional outlier detection;METRON;2020-08-03

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