予測パターンマイニングモデルの最適化アルゴリズム

抄録

In various data analysis tasks, modeling patterns such as sets, series, and graphs as features is useful not only for improving prediction performance, but also for knowledge extraction. However, considering all possible combination of patterns exponentially increases the number of model parameters, making it difficult to train models using ordinary optimization algorithms. In this study, we introduce an optimization algorithm that uses convex optimization and pattern mining approaches to efficiently train predictive pattern mining models.