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Notably, the target-present condition is most similar to the methods of Watanabe et al., [7] and here it is this condition that showed the most robust learning effect.
The rat strain that we used is the Long Evans rats which are known to exhibit most robust learning performances in all laboratory rodent species and they are the favorite strain for many neuroscientists who conduct in vivo recording experiments.
Many different shock paradigms (e.g., continuous weak shock vs. short strong shock) can be tested to determine which one results in the most robust learning for a particular type of experiment.
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In the present study the most robust generalization of learning was to complex cognitive measures.
Finally, most contractors have a robust learning platform for employee education, should anyone fail a phishing test.
FS is a machine learning-based technique used to select the most important features for building a robust learning model.
According to Kantardzic [18], feature selection is a set of techniques that select relevant features (PMFCC sub concepts) for building robust learning models by removing most irrelevant and redundant features from the data.
The most robust result without exception is that onset learning does not generalise to offset timing under any circumstances and that offset timing judgments, in all cases, are made with very low acuity relative to onset timing precision.
This strategy has been labelled as "one of the most robust across the entire history of experimental research on learning and memory" (pdf).
This prediction holds across most domains of cognitive ability, but verbal learning and verbal memory show the most robust effects [ 93, 97, 99].
We have reviewed three different cases: in the first one, the random forest and SVM classifiers have been applied in conjunction with data pre-processing and cost-sensitive learning with the objective of finding the most robust solution.
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CEO of Professional Science Editing for Scientists @ prosciediting.com