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Exact(5)

A model has been trained based on user and tweet characteristics using supervised learning for identifying misinformation in Twitter (accuracy ~77%) [37].

A model (MLlib's logistic regression) has been trained based on context specific grammars for predicting sentiment polarity of internet movie database (IMDb) reviews [43], which achieved ~64%% accuracy.

It is interesting to note that phi angle predictions are obviously more accurate than psi angle predictions, although the predictors have been trained based on the same set of proteins with the same set of features.

After parameters have been trained based on positive and negative samples, all hypothetical proteins would be decided to be genuine genes or falsely annotated non-coding sequences.

A simple ANN model has been trained based on the experimental data of ketone reduction reactors and used as an efficient prediction tool for assessing their performance.

Similar(55)

For each sequence, an AAM was trained based on exactly one stride, using the provided landmark data.

As an illustration, for the traditional classification-based QSAR models, they are trained based on a set of molecules with known classification labels for a given target.

Since QRNN is trained based on temporally simultaneous features, it cannot be utilized directly in forecasting one year ahead because some features, like hourly temperature in the next year, cannot be foreseen.

Essentially, the networks are trained based on parallel sets of mixtures and their constituent target sources.

A single model was trained based on activity data from ChEMBL exclusively.

Various NN structures were trained based on the back-propagation feed-forward approach.

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