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Systems, apparatus, and methods for generating prediction sets based on a known set of features
Systems, apparatus, and methods for generating prediction sets based on a known set of features
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机译:基于已知一组特征生成预测集的系统,装置和方法
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摘要
An individual having a plurality of first features and a second characteristic is identified. A plurality of second features associated with a second characteristic is determined. For each first feature among the plurality of first features, a respective probability distribution indicating, for each respective second feature, a probability that a person having the respective second feature has the first feature, is determined, thereby generating a plurality of probability distributions. A probabilistic classifier is used to combine the plurality of probability distributions, thereby generating a merged probability distribution. A Monte Carlo method is used to generate a prediction set based on the merged probability distribution, the prediction set including a plurality of prediction values for the second characteristic of the individual, each respective prediction value being associated with one of the plurality of second features. The prediction set is stored in a memory. The probabilistic classifier may include a Naïve-Bayes method. Prediction sets may be generated for each of a plurality of individuals, and used to predict a feature associated with a group. For example, an advertisement may be selected and displayed based on the predicted feature.
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机译:鉴定具有多个第一特征和第二特征的个体。确定与第二特征相关联的多个第二特征。对于多个第一特征中的每个第一特征,确定指示每个相应的第二特征的相应概率分布,所以具有相应的第二特征的人具有第一特征的人具有第一特征的概率,从而产生多个概率分布。概率分类器用于组合多个概率分布,从而生成合并的概率分布。 Monte Carlo方法用于基于合并概率分布生成预测集,该预测集包括用于各个的第二特征的多个预测值,每个相应的预测值与多个第二特征中的一个相关联。预测集存储在存储器中。概率分类器可包括Naïve-贝叶斯方法。可以为多个个体中的每一个生成预测集,并且用于预测与组相关联的特征。例如,可以基于预测特征选择和显示广告。
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