首页> 外国专利> HIERARCHICAL LATENT VARIABLE MODEL ESTIMATION DEVICE, HIERARCHICAL LATENT VARIABLE MODEL ESTIMATION METHOD, SUPPLY AMOUNT PREDICTION DEVICE, SUPPLY AMOUNT PREDICTION METHOD, AND RECORDING MEDIUM

HIERARCHICAL LATENT VARIABLE MODEL ESTIMATION DEVICE, HIERARCHICAL LATENT VARIABLE MODEL ESTIMATION METHOD, SUPPLY AMOUNT PREDICTION DEVICE, SUPPLY AMOUNT PREDICTION METHOD, AND RECORDING MEDIUM

机译:分层潜在变量模型估计装置,分层潜在变量模型估计方法,供应量预测装置,供应量预测方法和记录介质

摘要

An main object is to provide a hierarchical latent variable model estimation device, a hierarchical latent variable model estimation method, a supply amount prediction device, a supply amount prediction method, and a recording medium that can solve the aforementioned problems. A hierarchical latent structure setting unit 82 sets a hierarchical latent structure that is a structure in which latent variables are represented by a tree structure and components representing probability models are located at nodes of a lowest level of the tree structure. A variational probability computation unit 81 computes a variational probability of a path latent variable that is a latent variable included in a path linking a root node to a target node in the hierarchical latent structure. A component optimization unit 83 optimizes each of the components for the computed variational probability. A gating function optimization unit 84 optimizes a gating function model that is a model for determining a branch direction according to the multivariate data in a node of the hierarchical latent structure, based on the variational probability of the latent variable in the node.
机译:主要目的是提供一种能够解决上述问题的分层潜变量模型估计设备,分层潜变量模型估计方法,供应量预测设备,供应量预测方法和记录介质。分层潜在结构设置单元82设置分层潜在结构,该分层潜在结构是其中潜在变量由树结构表示并且表示概率模型的分量位于树结构的最低级别的节点处的结构。变化概率计算单元81计算路径潜在变量的变化概率,该路径潜在变量是包括在分层潜在结构中的将根节点链接到目标节点的路径中的潜在变量。分量优化单元83针对计算出的变化概率来优化每个分量。选通函数最优化单元84基于节点中潜在变量的变化概率,对选通函数模型进行优化,该选通函数模型是用于根据分层潜在结构的节点中的多元数据来确定分支方向的模型。

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