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Prediction model learning apparatus, prediction model learning method, and computer program

机译:预测模型学习装置,预测模型学习方法和计算机程序

摘要

PROBLEM TO BE SOLVED: To provide technology for generating a model capable of highly accurate prediction even when some of explanatory variables included in training data is lost.SOLUTION: In the case of machine learning of a model conducted on the basis of training data in which samples composed of a pair of objective variable and explanatory variable are collected, the machine learning using a plurality of prediction models set for each group of samples of the training data that is divided into a plurality of groups, a use rate calculation unit 14 calculates, using an estimated parameter, a use rate of each of the prediction models constituting a model to be outputted for a lost pattern indicating a loss of component in an explanatory variable vector. An estimation unit 13 estimates a parameter of each prediction model by using the use rate of each prediction model for the lost pattern. A process performed by the use rate calculation unit 14 and a process performed by the estimation unit 13 using the use rate of each prediction model calculated by the process are alternately repeated by an instruction unit 15.
机译:解决的问题:提供一种即使在训练数据中包含的某些解释变量丢失时也能生成高度准确预测的模型的技术解决方案:在基于训练数据进行模型的机器学习的情况下,收集由一对目标变量和解释变量组成的样本,使用为训练数据样本的每一组设置的多个预测模型进行机器学习,训练数据样本分为多个组,使用率计算单元14计算使用估计的参数,构成要输出的预测模型的每个预测模型的使用率,用于指示指示变量矢量中的成分损失的损失模式。估计单元13通过使用每个预测模型对丢失图案的使用率来估计每个预测模型的参数。使用率计算单元14执行的处理和估计单元13使用通过该处理计算出的每个预测模型的使用率执行的处理由指令单元15交替地重复。

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