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Active learning [4, 13, 33, 36] is a particular form of supervised learning where instances to label are selected by the learner through some criteria aimed at reducing the label complexity [22], i.e., the number of label requests that are necessary and sufficient to learn the target concept.
A worthwhile goal for industry and regulatory authorities should be the reduction of reducing the label information asymmetry from one country to another especially in Europe under the EU and among all countries in order to facilitate trade.
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Active learning is concerned with learning accurate classifiers by choosing which examples will be labelled, reducing the labelling effort and the cost of training an accurate model.
Triflate exchange would scramble all 12 oxygen atoms in the triflyloxy and triflate groups further reducing the labelling in ions 6 a. 24 Therefore, for a 1 1 2 mixture of [ O]-5, [ O]-15 and Tf2O undergoing triflate-mediated O-exchange, the theoretical O-enrichment in product sulfoxides 5 and 15 should be less than 8%% (i.e., 92 % O÷12 oxygen atoms=7.7%%).
Compared with the well-known KIS encoding scheme, the proposed LRC-based scheme can reduce the label size significantly.
Furthermore, this must be achieved with a reduced number of labeled instances in order to reduce the labeling effort.
That the subscription-service operators are a powerful oligopoly further reduces the labels' bargaining power.
Advertising Age has noted with glee that in recent weeks the Grey Lady has reduced the labels that distinguish the articles placed on its site at the behest of advertisers from those which arose from the newsroom.
D-Confidence performs better in imbalanced datasets where it provides significant gains that greatly reduce the labeling effort.
D-Confidence reduces the labeling effort and identifies exemplary cases for all classes faster than confidence and farthest-first alone.
Active learning allows asking an oracle to label new instances, which are selected by criteria, aiming to reduce the labeling effort.
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