587,128 research outputs found
Augmented sparse principal component analysis for high dimensional data
We study the problem of estimating the leading eigenvectors of a
high-dimensional population covariance matrix based on independent Gaussian
observations. We establish lower bounds on the rates of convergence of the
estimators of the leading eigenvectors under -sparsity constraints when an
loss function is used. We also propose an estimator of the leading
eigenvectors based on a coordinate selection scheme combined with PCA and show
that the proposed estimator achieves the optimal rate of convergence under a
sparsity regime. Moreover, we establish that under certain scenarios, the usual
PCA achieves the minimax convergence rate.Comment: This manuscript was written in 2007, and a version has been available
on the first author's website, but it is posted to arXiv now in its 2007
form. Revisions incorporating later work will be posted separatel
Development of Electronic Data Processing /EDP/ augmented management system
To tailor the existing Unified Flight Analysis System to management data rather than technical data, a pilot model could be produced in breadboard form, using electronic data processing, in a matter of a few months at very moderate cost. Such a system lends itself to continuous refinement
A New Hierarchical Redundancy Eliminated Tree Augmented Naive Bayes Classifier for Coping with Gene Ontology-based Features
The Tree Augmented Naive Bayes classifier is a type of probabilistic
graphical model that can represent some feature dependencies. In this work, we
propose a Hierarchical Redundancy Eliminated Tree Augmented Naive Bayes
(HRE-TAN) algorithm, which considers removing the hierarchical redundancy
during the classifier learning process, when coping with data containing
hierarchically structured features. The experiments showed that HRE-TAN obtains
significantly better predictive performance than the conventional Tree
Augmented Naive Bayes classifier, and enhanced the robustness against
imbalanced class distributions, in aging-related gene datasets with Gene
Ontology terms used as features.Comment: International Conference on Machine Learning (ICML 2016)
Computational Biology Worksho
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