PROBABILITY DENSITY FUNCTION ESTIMATION DEVICE, CONTINUOUS VALUE PREDICTION DEVICE, METHOD, AND PROGRAM
PROBLEM TO BE SOLVED: To enable estimation of a correct probability density function that represents continuous value data generated by an individual.SOLUTION: A topic estimation unit 24 estimates a topic to which each continuous value dataset belongs, and then estimates a hyper parameter indicative...
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Language | English Japanese |
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07.12.2017
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Abstract | PROBLEM TO BE SOLVED: To enable estimation of a correct probability density function that represents continuous value data generated by an individual.SOLUTION: A topic estimation unit 24 estimates a topic to which each continuous value dataset belongs, and then estimates a hyper parameter indicative of a distribution of weight of each individual with respect to each topic, and a hyper parameter indicative of a distribution of shape parameters that characterize a histogram for each topic. An individual probability density function estimation unit 26 estimates the shape parameters for each topic and weight of each individual with respect to each topic in accordance with posterior probability of the shape parameters and posterior probability of the weight, and outputs, for each individual, a probability density function for the respective continuous value dataset generated by the individual, which is represented as a linear sum of histograms for the topics, each histogram being based on the estimated shape parameters for a respective topic, derived using the estimated weight of each individual for the respective topic.SELECTED DRAWING: Figure 1
【課題】個体が生成する連続値データを表す正しい確率密度関数を推定することができる。【解決手段】トピック推定部24が、各連続値データについて、所属するトピックを推定し、各個体の各トピックに対する重みの分布を表すハイパーパラメータと、各トピックに対するヒストグラムを特徴付ける形状パラメータの分布を表すハイパーパラメータとを推定する。個体確率密度関数推定部26が、形状パラメータの事後確率、及び重みの事後確率に従って、各トピックに対する形状パラメータ、及び各個体の各トピックに対する重みを推定し、各個体について、推定された各トピックに対する前記形状パラメータに基づく各トピックに対するヒストグラムの、推定された個体の各トピックに対する重みを用いた線形和で表される、個体が生成する連続値データの確率密度関数を出力する。【選択図】図1 |
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AbstractList | PROBLEM TO BE SOLVED: To enable estimation of a correct probability density function that represents continuous value data generated by an individual.SOLUTION: A topic estimation unit 24 estimates a topic to which each continuous value dataset belongs, and then estimates a hyper parameter indicative of a distribution of weight of each individual with respect to each topic, and a hyper parameter indicative of a distribution of shape parameters that characterize a histogram for each topic. An individual probability density function estimation unit 26 estimates the shape parameters for each topic and weight of each individual with respect to each topic in accordance with posterior probability of the shape parameters and posterior probability of the weight, and outputs, for each individual, a probability density function for the respective continuous value dataset generated by the individual, which is represented as a linear sum of histograms for the topics, each histogram being based on the estimated shape parameters for a respective topic, derived using the estimated weight of each individual for the respective topic.SELECTED DRAWING: Figure 1
【課題】個体が生成する連続値データを表す正しい確率密度関数を推定することができる。【解決手段】トピック推定部24が、各連続値データについて、所属するトピックを推定し、各個体の各トピックに対する重みの分布を表すハイパーパラメータと、各トピックに対するヒストグラムを特徴付ける形状パラメータの分布を表すハイパーパラメータとを推定する。個体確率密度関数推定部26が、形状パラメータの事後確率、及び重みの事後確率に従って、各トピックに対する形状パラメータ、及び各個体の各トピックに対する重みを推定し、各個体について、推定された各トピックに対する前記形状パラメータに基づく各トピックに対するヒストグラムの、推定された個体の各トピックに対する重みを用いた線形和で表される、個体が生成する連続値データの確率密度関数を出力する。【選択図】図1 |
Author | KIM HIDEAKI SAWADA HIROSHI |
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DocumentTitleAlternate | 確率密度関数推定装置、連続値予測装置、方法、及びプログラム |
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Snippet | PROBLEM TO BE SOLVED: To enable estimation of a correct probability density function that represents continuous value data generated by an individual.SOLUTION:... |
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Title | PROBABILITY DENSITY FUNCTION ESTIMATION DEVICE, CONTINUOUS VALUE PREDICTION DEVICE, METHOD, AND PROGRAM |
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