Add to ORKGPrincipal curves are parameterized curves passing "through the middle" of a data cloud. These objects constitute a way of generalization of the notion of first principal component in Principal Component Analysis. Several definitions of principal curve have been proposed, one of which can be expressed as a least-square minimization problem. In the present paper, adopting this definition, we study a Gaussian model selection method for choosing the length of the principal curve, in order to avoid interpolation, and obtain a related oracle-type inequality. The proposed method is practically implemented and illustrated on cartography problems
Principal components are a well established tool in dimension reduction. The extension to principal ...
In this work, basic theory and some proposed developments to localised principal components and curv...
Principal curves have been defined as “self consistent ” smooth curves which pass through the “middl...
Principal curves are nonlinear generalizations of the notion of first principal component. Roughly, ...
Abstract – Principal curves are nonlinear generalizations of the notion of first principal component...
Principal curves are defined as parametric curves passing through the ``middle'' of a probability di...
Principal curves and manifolds provide a framework to formulate manifold learning within a statistic...
When confronted with massive data streams, summarizing data with dimension reduction methods such as...
In this paper, we propose a method to build a sequence of generalized empirical principal curves, wi...
AbstractÐPrincipal curves have been defined as ªself-consistentº smooth curves which pass through th...
Principal curves have been defined as “self consistent ” smooth curves which pass through the “middl...
© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommo...
The subjects of this thesis are unsupervised learning in general, and principal curves in particular...
AbstractPrincipal curves have been defined as smooth curves passing through the “middle” of a multid...
peer reviewedWe propose an incremental method to find principal curves. Line segments are fitted and...
Principal components are a well established tool in dimension reduction. The extension to principal ...
In this work, basic theory and some proposed developments to localised principal components and curv...
Principal curves have been defined as “self consistent ” smooth curves which pass through the “middl...
Principal curves are nonlinear generalizations of the notion of first principal component. Roughly, ...
Abstract – Principal curves are nonlinear generalizations of the notion of first principal component...
Principal curves are defined as parametric curves passing through the ``middle'' of a probability di...
Principal curves and manifolds provide a framework to formulate manifold learning within a statistic...
When confronted with massive data streams, summarizing data with dimension reduction methods such as...
In this paper, we propose a method to build a sequence of generalized empirical principal curves, wi...
AbstractÐPrincipal curves have been defined as ªself-consistentº smooth curves which pass through th...
Principal curves have been defined as “self consistent ” smooth curves which pass through the “middl...
© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommo...
The subjects of this thesis are unsupervised learning in general, and principal curves in particular...
AbstractPrincipal curves have been defined as smooth curves passing through the “middle” of a multid...
peer reviewedWe propose an incremental method to find principal curves. Line segments are fitted and...
Principal components are a well established tool in dimension reduction. The extension to principal ...
In this work, basic theory and some proposed developments to localised principal components and curv...
Principal curves have been defined as “self consistent ” smooth curves which pass through the “middl...