… special case of clustering problem, … clusters are always subsequences of the dataset. The
main contribution of this work is a new heuristic clustering method, based on the principal curve…

… its good capacity of data representation and clustering, ie, the principal curve is able to fit any
… the curve are minimized and (ii) the method is able to give us an idea of how many clusters …

… -PCC) for refining a principal curve clustering based on the … and Raftery [5] and an initial
clustering method such as MCLUST [4], … and analyzed with principal curve clustering; this would …

… novel clustering method for functional data based on the principal curve clustering approach…
approximated using functional principal component analysis (FPCA) and the principal curve …

… method for data clustering based on principal curves is presented. Principal curves consist
of a … , a novel method for data clustering is proposed, which is based on principal curves [2]. …

… some background on principal curves and introduce our probability model and clustering
algorithm. Section 2.3 presents our method for clustering on open principal curves, and Section …

… to one-dimensional curves, and then define the principal curves of smooth probability
distributions in p space. Subsequent sections give algorithms for finding the curves, both for distribu…

… K-means clustering method for analysing ICCs and IICs via the functional principal component
analysis. We show that the combined use of FDA and cluster analysis reveals interesting …

… principal curves in clustering to complex multidimensional datasets. The use of principal curve
in clustering … complexity data Automatic parameterization of the principal curve to assure …

… of the principal curves and surfaces, as well as a unifying view for clustering, principal curve
… In summary, our KDE based principal curve projection algorithm not only connects the trade …