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The use of the auxiliary data as training for the MaxEnt model.
These include: The use of the auxiliary data as training for the MaxEnt model One more step to rebuild the unsupervised lexica/chunks with insights from the model's feature weights Taking advantage of the division into topics and of the provided meta-data.
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In the inference process for these predictions, we used all the known drugs and target proteins in the gold standard data as training data, and predicted potential interactions for all compounds in KEGG LIGAND and all the other drugs in KEGG DRUG (the drugs are absent from the gold standard data).
Some data are used as training data for establishing classification model for throat polyp detection with SVM algorithm.
For example, inaccurate subcellular localization assignments could be propagated if the data were used as training data for a machine learning method by researchers unfamiliar with the field.
These pairs are added to the labeled list and (together with the original set of labeled data) are used as training data for the next iteration.
This sampled data is then used as training data for artificial neural network, which will act as a metamodel to represent the time consuming disciplinary analyses.
We used this data as the training compendium for EPSA.
ED data from 2/1/94 – 5/31/02 is used as training data for least squares fitting to establish control limits; data from 6/1/02 – 53/31/03 is then used in near real time surveillance.
Necessary adjustments and/or refinements on the data collection process and data collection forms as well as further training for research nurses to facilitate reliable data collection will be made prior to the main study.
The SVM predictors were given these data as input for training and were classifying peaks as overlapping or not (that is, cell-type specific).
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