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phishGILLNET3 is the only method that handles unlabeled data.

New feature extraction method that handles nonlinearly separable datasets, preserves data geometry, minimises classification error directly and is designed especially for visualisation is suggested.

First, we present the results obtained by the method of moments, that has a higher level of approximation, and later, the results by the histogram method that handles raw data.

In the presented study, orthogonal projection to latent structures (OPLS) is introduced as a data preprocessing method that handles nonlinear data prior to modelling with two well established nonlinear multivariate models; namely support vector regression (SVR) and artificial neural networks (ANN).

We present a highly-parallel multi-frequency hybrid radiation hydrodynamics algorithm that combines a spatially-adaptive long characteristics method for the radiation field from point sources with a moment method that handles the diffuse radiation field produced by a volume-filling fluid.

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In our previous work[18], we introduced a kernel-based image upscaling method that handled the ringing artifact problem caused by using a wider window for the Lanczos kernel.

Also, perturbation methods that handle the dramatic effects of small disorder are developed to analyze eigenvalue loci veering and strong localization.

More methods that handle genetic heterogeneity and complexity should be developed to utilize genomic information fully for gene mapping.

In this review we will focus on data analysis methods that handle two-way data.

Results: We present a generative statistical model and associated inference methods that handle read mapping uncertainty in a principled manner.

Applying statistical methods that handle missing data appropriately may reduce the bias and increase the precision of the estimates obtained [ 3].

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