Study effectiveness of k-means clustering of functional data: functional principal component scores feature and mean curve feature
碩士 === 國立臺灣大學 === 數學研究所 === 99 === Organizing functional data into sensible groupings is one of the most fundamental modes of understanding and learning the underlying mechanism generating functional data. Clustering analysis is often employed to search for homogeneous subgroups of individuals in a...
Main Authors: | Chia-Tung Chiang, 江家彤 |
---|---|
Other Authors: | Hung Chen |
Format: | Others |
Language: | en_US |
Published: |
2011
|
Online Access: | http://ndltd.ncl.edu.tw/handle/95180268728241580134 |
Similar Items
-
The investigation of TB patients features with K-Means clustering
by: Farzad Firuzi Jahantigh, et al.
Published: (2015-12-01) -
Machine Tool Volumetric Error Features Extraction and Classification Using Principal Component Analysis and K-Means
by: Kanglin Xing, et al.
Published: (2018-09-01) -
Entropy K-Means Clustering With Feature Reduction Under Unknown Number of Clusters
by: Kristina P. Sinaga, et al.
Published: (2021-01-01) -
K-means clustering based filter feature selection on high dimensional data
by: Dewi Pramudi Ismi, et al.
Published: (2016-03-01) -
A Study on Feature Selection and Fast k-Means Clustering Algorithms
by: Jinhua Chang, et al.
Published: (2000)