Sentence examples for by the learning set from inspiring English sources

Thorough cross-validation tests are needed in order to assess whether the score function is stably parameterized by the learning set.

The function was normalized by centring the learning set of healthy controls on 1 and that of Alzheimer's disease patients on −1.

The method chosen for taking this point into account was to build the learning set by exhaustively selecting all infected patients and by random sub-sampling of non-infected patients.

Once defined, the model was applied to expression data to assign the "IBC-like" or the "nIBC-like" class: first for testing its robustness by leave-one-out cross-validation [54] in the learning set and by validation in an independent set of 24 IBC and nIBC samples, then for estimating its prognostic value in public nIBC datasets.

A probability score of ≥0.5 is assigned to all the disease proteins in the learning set used by DGP.

As summarized in Table 2, 10 out of the 239 (4.2%) sites from the learning set were not predicted by pkaPS.

Thus, the CV score is obtained by sampling the learning set and the testing set several times, and taking the expectation of the likelihood over these replicates (parameters being inferred from the training tests): CV = E [ − ln p (D T | θ ^ L ) ] By averaging over replicates, one gets rid of sampling errors in the partitioning of the dataset into a learning set and a test set.

The pattern recognition was more efficient when the learning set was extended by non-unitary matrices.

To prevent the NTI from being dependent on the learning sets, the whole process was repeated a hundred times (always by choosing the learning sets at random).

Since we do not have control over the learning sets of the competing tools, performance of these tools is likely to be positively affected by overlaps between their learning sets and our test sets.

It is based on a "learning phase," where a large number of "known points," with known input and output values, are used to train the neural network system in an "optimal" way, so that it can be later used to predict (unknown) output values for a new set of input values, that should fall in the domain of the hyperspace that is properly sampled by the learning data set.