With the development of the Deep Learning, it becomes more important to verify what methods are valid for the prediction of time series data. In this study, we propose a new method of time series prediction, using mulitiple deep learners and a Baysian network. In this paper, training data is divided into some clusters with K-means clustering and the multiple deep learners are trained, depending on each clusters. A naive Bayes classifier is used to determine which the deep learner is in charge

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... predicting a time series. Our proposed method is applied to financial time series data, and the predicted results for the Nikkei 225 is demonstrated.