In this article, we adapt the well-known emerging-pattern--based classification models and propose a semi-streaming approach. For streaming features, it is ...

Many datasets from real-world applications have very high-dimensional or increasing feature space. It is a new research problem to learn and maintain a ...

This paper proposes a novel algorithm about online streaming feature selection, named ConInd that uses a three-layer filtering strategy to process streaming ...

The empirical study clearly shows that our method not only achieves high accuracy, but also takes less CPU time than the existing classification methods. Most.

We evaluate the effectiveness and efficiency of the proposed method using a series of benchmark datasets and a real-world case study on Mars crater detection.

We evaluate the effectiveness and efficiency of the proposed method using a series of benchmark datasets and a real-world case study on Mars crater detection.

In most of the real time data stream application data usually reach very rapidly that flows continuously in real time environment .This incoming data streams ...

Missing: Features: Approach.

This paper presents a new technique on mining emerging patterns using streaming feature selection by exploiting the relationship between feature relevance ...

In this paper, we propose mining Jumping Emerging Patterns by Streaming Feature selection (JEPSF for short) using a dynamic border-differential algorithm where ...