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We use two approaches to deal with the imbalance problem: sampling methods and cost-sensitive learning.
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The two-phase framework can be applied in missing data problems, sampling at multiple occasions, and situations without a good frame.
"I have a gift for getting things to work with problem samples," Dr. Constable said.
Computational Diffie-Hellman (CDH) problem: Sample: (P ,a, P b Pfor some (a,b in Z_{q}^).
This paper illustrates the correlation between a fixed problem sample size, SPE ratio and processing element (PE) architecture for a target implementation in 130-nm CMOS technology.
To circumvent this problem, samples were first embedded in epoxy resin and left in the dark for 48 h until full polymerization.
Decisional Diffie-Hellman (DDH) problem: Sample: (P,a P,b P,c P) for some (a,b,c in Z_{q}^).
To alleviate this problem, samples re-dissolved in 1 M NaOH were added with 100 μL HCl before undergoing NMR analyses.
Observations of many classification problems with different classification methods have shown that although there is usually a best method for a specific problem, samples that are correctly classified or misclassified by different methods may not necessarily overlap [33].
However, such multiple samples may lead to another problem: sample dependence of outputs [ 26].
Some problem samples were extracted using a Genomic DNA Mini Kit I Multi (Animal/Plant) (Koma Biotech Inc).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com