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ADAPTIVE SAMPLING TECHNIQUE FOR SELECTING NEGATIVE EXAMPLES FOR ARTIFICIAL INTELLIGENCE APPLICATIONS
ADAPTIVE SAMPLING TECHNIQUE FOR SELECTING NEGATIVE EXAMPLES FOR ARTIFICIAL INTELLIGENCE APPLICATIONS
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机译:为人工智能应用选择负例的自适应采样技术
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摘要
Artificial intelligence applications require use of training sets containing positive and negative examples. Negative examples are chosen using distributions of positive examples with respect to a dominant feature in feature space. Negative examples should share or approximately share, with the positive examples, values of a dominant feature in feature space. This type of training set is illustrated with respect to content recommenders, especially recommenders for television shows.
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