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Many algorithms have been developed for remote estimation of the leaf area index of vegetation, such as using spectral vegetation indices, inversion of radiative transfer models, and supervised learning techniques.

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For linear modeling and supervised inferences, we used the package "limma" [ 62].

These include robust estimation of mean and covariance in high dimensions, robust learning of various latent variable models, and robust supervised learning.

The first is the way in which sites, or local protein microenvironments, are represented; the second part concerns model building and supervised machine learning methods; and the third involves site scoring and model evaluation.

J. A. Onofrey, L. H. Staib and X. Papademetris, Low-Dimensional Non-rigid Image Registration Using Statistical Deformation Models and Semi-Supervised Learning, IEEE Trans.

SVM is a kind of two-stage classification model and a supervised machine learning method.

JW performed the mathematical modelling and analysis, supervised by TS.

The best overall performance was obtained by combining the strengths of a syntactic parser (i.e. ENJU-Genia), a relation classification model, and a supervised classification model.

There are a wide range of algorithms and models for supervised learning and context recognition.

To demonstrate its discrimination capability, unsupervised and supervised classification models have been built and validated.

Students with prior exposure to linear algebra, statistical theory and convex optimization learn an integrated understanding of the underlying principles and potential applications of kernel-based unsupervised and supervised learning models.

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