labeled data


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labeled data

(1) A text file that contains data identified with an embedded tag. See tagged text and XML.

(2) A multimedia file that contains a description of its content. Such files provide a supply of samples for a deep learning system. See deep learning, metadata and tagged text.
References in periodicals archive ?
In all of the classifiers, the accuracy increased as more labeled data were used, and it reached above 90% when greater than 200K labeled data were used.
To date, "most of the stuff out there right now is incredibly data-hungry and relies exclusively on correlations and not heuristics," said Medina, who also noted that because ML is correlation-based, it needs enormous amounts of clean, labeled data to be trained.
Initially, the method applies active learning for the labeled data and then a semisupervised regularization process is designed for the remaining unlabeled data.
Therefore, how to adapt the classifier trained by the old labeled data to the identification of new samples is a difficult problem in on-line identification [10-13].
One drawback has been paucity of labeled data. Techniques to augment training set by automated process is also being addressed here.
Finally, many Gizmos generate data that is accessible on a second tab found at the top of the Gizmo, typically labeled Data.
An advantage of Comrafs is that they offer a unique intrinsic method for incorporating labeled data which does not require significant changes in the model.
where [OMEGA](x) is any increasing monotonic function and [theta] > 0 is the trade-off between the distribution mismatch and the structural risk function R(f, k, D) on the labeled data.
The DBN uses a fast, greedy unsupervised learning algorithm to train RMBs and a supervised fine-tuning method to adjust the network by labeled data [38].
By distant supervision, we can derive automatic labeled data of an associated sentence with such drug event, for example, "His ramipril were discontinued due to allergy and added to list in our medical records," "ADR," and known as instance-level relation.
First, these methods are based on resampling of labeled data for generating individual classifiers, therefore, they cannot deal with semi-supervised learning where the number of available labeled data is usually small.