Prediction program using decision tree learning algorithm, apparatus and method

摘要

PROBLEM TO BE SOLVED: To provide a prediction program, device and method capable of enhancing prediction accuracy in a prediction model even in learning with a teacher, such as a decision tree learning algorithm and even though there is a change in teacher data in the latest short period to a huge amount of teacher data in a past long period.SOLUTION: As a learning step, a decision tree learning algorithm calculates the contribution degree of each explanatory variable with a whole explanatory variable group as teacher data, and acquires the first prescribed number of first explanatory variable groups from a high level in the descending order of contribution degrees. Next, a second explanatory variable group acquired in time series for the latest short period is acquired in each explanatory variable included in the first explanatory variable groups. Next, the contribution degree of each explanatory variable is calculated by the decision tree learning algorithm with the second explanatory variable group as teacher data. Next, the second prescribed number of third explanatory variable groups is extracted from a high level in the descending order of contribution degrees. Then, a prediction model in the decision tree learning algorithm is created with the third explanatory variable groups as teacher data.SELECTED DRAWING: Figure 2