Sentence examples for methods are trained from inspiring English sources

While energy-based methods use physical, statistical, or empirical energy functions to estimate the stability change from the protein's three-dimensional structure [ 2- 9], training-based methods are trained on the experimental data from the ProTherm database [ 10] employing machine learning algorithms [ 11- 26].

Supervised methods are trained on examples with labels (for example, 'gene' or 'not gene') and are then used to predict these labels on other examples, whereas unsupervised methods find patterns in data sets without the use of labels.

In order to improve accuracy of the scoring functions used in BINDSURF we propose a hybrid novel approach where neural networks (NNET) and support vector machines (SVM) methods are trained with databases of known active (drugs) and inactive compounds, being this information exploited afterwards to improve BINDSURF VS predictions.

Some methods are trained with already published RREs, whereas others identify de novo RREs.

Computational methods are trained on these types of disease data, and so detect loss of activity greater than that magnitude.

However, as we pointed out earlier, [ 18] it isn't a good practice, since most of the methods are trained only on TMPs and not on mixed sets of TMP and non-TMP sequences.

All benchmark machine learning methods were trained on the same input data as described for our method (normalised adjacency with enriched properties of known causes of each ADR).

The predictions generated by previously published methods will depend on the input features, so these methods were trained on the same input features as used with our method, and their prediction performance was evaluated with the same EHR pipeline.

The methods were trained on 30% of these points and tested on the remaining 70%, and results were also compared with existing land cover products.

For fair comparison, different machine learning methods were trained with the same training sets and tested with the same testing sets.

Methods were trained using nine subsets and tested using the remaining subset.