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We developed machine learning-based systems, based on conditional random fields (CRF) and structured support vector machines (SSVM) respectively, for the CEM task for this data set.
Most of the systems were hybrid systems using machine learning techniques based on conditional random fields (CRFs) that exploited also chemical dictionaries as one of the used lexical features.
The tagger is based on Conditional Random Fields (CRF) [4] models, with additional rules for pre and post processing documents.
In this work, we propose an annotation system, based on Conditional Random Field (CRF) models, for the identification of chemical and drug names in scientific texts.
Klinger [7] implemented a new machine learning approach based on Conditional Random Fields (CRF) to detect IUPAC and IUPAC-like chemical names in the scientific literature and obtained good performance: an F measure of 85.6% on a MEDLINE [15] corpus.
The recursive neural network architecture is able to predict hierarchical tree structures for scene images, and outperforms other methods based on conditional random fields or a combination of other methods, as well as outperforming other existing methods in segmentation, annotation and scene classification.
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Based on a conditional random forest consisting of 500 conditional random trees, variance importance scores were calculated to verify our findings.
Because it is extreme slow to find the best PrSM with two PTMs by searching a spectrum against a large random protein database with 10 proteins, the evaluation method based on conditional spectral probabilities was not used.
Various statistical analysis techniques, often based on conditional probabilties and/or Bayes theorem, allow us to make use of the information on jets despite the random errrors.
And these theories are mainly based on conditional, because the main assumptions concerns conditional reasoning.
One found a lower recall rate based on conditional recall.
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CEO of Professional Science Editing for Scientists @ prosciediting.com