Feature selection techniques are often used to reduce data dimensionality, increase classification performance, and gain insight into the processes that generated the data. In this paper, we describe an iterative procedure of feature selection and ...

The purpose of this study is to propose a new online and nonlinear PCA(OL-NPCA) method for feature extraction from the incremental data. Kernel PCA(KPCA) is widely used for nonlinear feature extraction, however, it has been pointed out that KPCA has the ...

A crucial issue for Machine Learning and Data Mining is Feature Selection, selecting the relevant features in order to focus the learning search. A relaxed setting for Feature Selection is known as Feature Ranking, ranking the features with respect to ...

This paper presents a novel method for finding interesting pass patterns from soccer game records. Taking two features of the pass sequence "temporal irregularity and requirements for multiscale observation" into account, we have developed a comparison ...

Effective incorporation of human expertise, while exerting a low cognitive load, is a critical aspect of real-life text classification applications that is not adequately addressed by batch-supervised high-accuracy learners. Standard text classifiers ...