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The input data for training this neural network were provided by the Taguchi method.
Therefore, these parameters were mainly used as input data for training and testing the ANN.
Biofilm growth characteristics (e. g. lag time, net accrual rate, peak biomass) recorded in dependency from external conditions may be used as input data for training of artificial neural networks (ANN) and mechanistic modelling.
The other learning scheme, the unsupervised learning, is worked in the manner that does not require any real physical data set for the training but rather exploits the statistical representation of the input data for training NN.
The aim of model evaluation is to obtain the error rate of model according to the input data for training purposes and it is based on various criteria of error calculation.
Furthermore, we use simultaneous shifts in the standard deviation of both x 1 and x 2 with random magnitude of shifts distributed uniformly in the range of δ i ∊ [1.5, 2.5]; i = 1, 2. Now, 4000 input data for training network A and B and 3000 ones for training network C are available.
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The input data for the HMM training is a set of observation vectors.
For different dosimetric materials, a series of experiments would have to be performed again to obtain input data for the proposed ANN training.
The input data for classification is a training set composed by a collection of records characterized by a tuple (x, y).
Let the training input data for a prediction model consist of a set X of drug target pairs x = (x d,x t) and their real-valued labels y (either binary or quantitative interaction affinities).
This model assumes independence between different evidences, in order to train the input data for predicting PPIs.
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