Add to ORKGLooking for curves similarity could be a complex issue characterized by subjective choices related to continuous transformations of observed discrete data (Chiodi, 1989). In this paper we combine the aim of finding clusters from a set of individual curves to the functional nature of data, applying a variant of a k-means algorithm based on the principal component rotation of data. We apply a classical clustering method to rotated data, according to the direction of maximum variance. A k-means clustering algorithm based on PCA rotation of data is proposed, as an alternative to methods that require previous interpolation of data based on splines or linear fitting (García-Escudero and Gordaliza (2005), Tarpey (2007), Sangalli et al. (200...
k-means algorithm is a popular data clustering algorithm. k-means clustering aims to partition n obs...
Procedures for oblique rotation of factors or principal components typically focus on rotating the p...
Principal component analysis (PCA) is a usefully tool for data compres- sion and information extract...
Looking for curves similarity could be a complex issue characterized by subjective choices related t...
Looking for curves similarity could be a complex issue characterized by subjective choices related t...
Similar features between waveform data recorded for earthquakes at different time instants could sug...
In this paper we focus on finding clusters of multidimensional curves with spatio-temporal structure...
In this paper we focus on finding clusters of multidimensional curves with spatio-tempora...
Principal axis analysis rotates principal components to optimally detect cluster structure, rotation...
Abstract. Looking for curves similarity could be a complex issue characterized by subjective choice...
Looking for curves similarity could be a complex issue characterized by subjective choices related t...
This paper proposes a new robust approach to nonlinear clustering based on the Principal Component A...
In this paper we propose a novel clustering method for functional data based on the principal curve ...
The problem of detecting clusters is a common issue in the analysis of functional data and some int...
Functional data can be clustered by plugging estimated regression coefficients from individual curve...
k-means algorithm is a popular data clustering algorithm. k-means clustering aims to partition n obs...
Procedures for oblique rotation of factors or principal components typically focus on rotating the p...
Principal component analysis (PCA) is a usefully tool for data compres- sion and information extract...
Looking for curves similarity could be a complex issue characterized by subjective choices related t...
Looking for curves similarity could be a complex issue characterized by subjective choices related t...
Similar features between waveform data recorded for earthquakes at different time instants could sug...
In this paper we focus on finding clusters of multidimensional curves with spatio-temporal structure...
In this paper we focus on finding clusters of multidimensional curves with spatio-tempora...
Principal axis analysis rotates principal components to optimally detect cluster structure, rotation...
Abstract. Looking for curves similarity could be a complex issue characterized by subjective choice...
Looking for curves similarity could be a complex issue characterized by subjective choices related t...
This paper proposes a new robust approach to nonlinear clustering based on the Principal Component A...
In this paper we propose a novel clustering method for functional data based on the principal curve ...
The problem of detecting clusters is a common issue in the analysis of functional data and some int...
Functional data can be clustered by plugging estimated regression coefficients from individual curve...
k-means algorithm is a popular data clustering algorithm. k-means clustering aims to partition n obs...
Procedures for oblique rotation of factors or principal components typically focus on rotating the p...
Principal component analysis (PCA) is a usefully tool for data compres- sion and information extract...