Abstract. Supervised learning on sequence data, also known as se- quence classification, has been well recognized as an impor- tant data mining task with ...

Dec 18, 2013 · A so-called early-prediction utility is defined and used to select features and rules. The generalized sequential decision tree (GSDT) method ...

We analyze the problem and the challenges. As the first attempt to tackle the problem, we propose two interesting methods. The sequential classification rule ( ...

The early time series classification method based on prefix was first proposed in the paper [18] . The idea is to obtain the MPL (Minimum Prefix Length, MPL) of ...

As the first attempt to tackle the problem, we propose two interesting methods. The sequential classification rule (SCR) method mines a set of sequential ...

We propose an alternative approach based on the use of objective machine learning pro- grams. To illustrate this approach we investigated the distribution of ...

Aug 9, 2022 · This study proposes a modeling methodology deploying interpretable Hidden Markov Model for mining of the sequential learning behavior built upon ...

Dec 15, 2022 · The main goal of this paper is to demonstrate that sequential pattern mining can be used to build models that can detect which students are ...

Sequence Classification Based on Delta-Free Sequential Patterns. Abstract: Sequential pattern mining is one of the most studied and challenging tasks in data ...

Jun 26, 2024 · Mining sequence classifiers for early prediction. In Proceedings of the 2008 SIAM international conference on data mining, pp. 644–655. SIAM ...