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Fortunately, they can be estimated using training packets in practical scenarios.
In practical scenarios, the parameter should be selected based on the physical layer outage probability which can be estimated using training packets.
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The weights were estimated using training samples and automatically adapted to testing data.
We showed how these probabilities can be estimated using the training dataset in an effective way.
Given a TCQ code-book, the probabilities P(B = b i |Ŷ = η k ) and P(Ŷ = η k |B = b i ) can be estimated using the training set [it is sufficient to estimate p i, k = P B = b i, Ŷ = η k ), k = 1, … Y, i = 1, …, N ].
It then predicts a resistant phenotype for samples containing resistant alleles of sufficiently high frequency, where 'sufficiently high' is estimated using the training set.
First, the parameters of the DRM are estimated using the training dataset (i.e., part of historical data).
The models are estimated using the training data set, and the model predictions are evaluated using the validation data set.
The enzymatic reaction rate for the defined maltose and glucose concentration was estimated using the trained network.
A family of model parameters was estimated using nine experimental training sets compiled from different cell-lines and laboratories.
The coefficients of QSAR model were estimated using this new training set which were then used for predicting the activity of the test compound.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com