Paper Title:
Natural Nearest Neighbor for Isomap Algorithm without Free-Parameter
  Abstract

Isomap is a classic and efficient manifold learning algorithm, which aims at finding the intrinsic structure hidden in high dimensional data. Only deficiency appeared in this algorithm is that it requires user to input a free parameter k which is closely related to the success of unfolding the true intrinsic structure and the algorithm’s topological stability. Here, we propose a novel and simple k-nn based concept: natural nearest neighbor (3N), which is independent of parameter k, so as to addressing the longstanding problem of how to automatically choosing the only free parameter k in manifold learning algorithms so far, and implementing completely unsupervised learning algorithm 3N-Isomap for nonlinear dimensionality reduction without the use of any priori information about the intrinsic structure. Experiment results show that 3N-Isomap is a more practical and simple algorithm than Isomap.

  Info
Periodical
Advanced Materials Research (Volumes 219-220)
Edited by
Helen Zhang, Gang Shen and David Jin
Pages
994-998
DOI
10.4028/www.scientific.net/AMR.219-220.994
Citation
X. L. Zou, Q. S. Zhu, R. L. Yang, "Natural Nearest Neighbor for Isomap Algorithm without Free-Parameter", Advanced Materials Research, Vols. 219-220, pp. 994-998, 2011
Online since
March 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Zhong Ping Zhang, Yong Xin Liang
Abstract:This paper proposes a new data stream outlier detection algorithm SODRNN based on reverse nearest neighbors. We deal with the sliding window...
1032
Authors: Wei Feng Wang, Jun Tao Yuan, An Lin Zhang, Meng Li
Chapter 5: Road and Bridge Engineering
Abstract:For present-day bridges.cable tensions test is a vitally important job in course of construction.The tensions condition of cables plays an...
1117
Authors: Dong Wang, Shi Huan Xiong
Chapter 8: Nanomaterials and Nanomanufacturing
Abstract:The learning sequence is an important factor of affecting the study effect about incremental Bayesian classifier. Reasonable learning...
1455
Authors: Na Rui Bu, Run Shan Bai, Zhang Zhen Li, De Zhong Lin
Chapter 6: Vibration, Noise Analysis and Control
Abstract:Analysis of slope stability based on BP neural network, the analytical model of slope stability is built. Aiming at the defects that BP...
1263
Authors: Xue Feng Wu, Yu Fan
Chapter 6: Mechatronics
Abstract:A new algorithms for parameters of an image irregular boundary circle parameters is presented, which is based on “Curve-Approximate Method”...
639