Yung-Hsing Chiu

Learn More
This paper proposes a parameter-free classifier which combines K-means with Nearest Neighbor Rule (NNR) called Incremental Cluster-based Classification (ICC). The classifier is used in low power and capacity devices such as Personal Digital Assistant (PDA) and Smartphone. In the training phase, ICC employs K-means to group instances into several clusters,(More)
Nearest neighbor rule (NNR) is a parameter-free classifier which is easy to implement, simple to operate and with high accuracy. However, it is time and memory consuming for large datasets. This study proposed a parameter-free method to accelerate NNR. This method employs a class-based clustering algorithm to divide the training data to several clusters(More)
Hierarchical Clustering (HC) is not designed to locate the leaf nodes in the tree structure, and therefore is not suitable to locate similarity relation on the sequence of the leaf nodes. In order to generate the similarity relation on tree structure diagram of HC, we proposed an improved solution in this paper; Referential Hierarchical clustering Algorithm(More)
One of the powerful classifiers is Support Vector Machine (SVM), which has been successfully applied to many fields. Despite its remarkable achievement, SVM is time-consuming in many situations where the data distribution is unknown, causing it to spend much time on selecting a suitable kernel and setting parameters. Previous studies proposed understanding(More)
  • 1