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Kernel based methods have achieved major success in building nonlinear classifiers [17].
These machine learning based methods have achieved promising predictive performances.
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The algorithms based on these methods have achieved good tracking performance, but relying on a single visual feature is often inadequate and unstable in some complex tracking scenarios.
These methods have achieved appropriate performance in classification.
These methods have achieved great success in the last two decades.
All these methods have achieved impressive classification performances.
Obviously, some other methods have achieved about 1% higher overall accuracy than our method.
Physically based method has been applied in fluid simulation for achieving vivid and high-quality visual image.
The method has achieved improved sensitivity and accuracy over the RNA z-test method (ie, ranking genes as targets based on normalized expression data, without any additional modelling or processing) and a competitive, alternative network-inference method, MNI [ 14].
Association rule-based classifiers have achieved accuracies equivalent to traditional SVM methods for common biological problems [ 71].
They urge us to practise only evidence-based medicine, by which they mean following rigid protocols based on treatments that have achieved positive results either in double-blind placebo-controlled drug trials, or meta-analyses (a method for grouping together results from several trials).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com