Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
The purpose of this paper is to study the problem of pattern classification as this is presented in the context of data mining. Among the various approaches we focus on the use of ...
Nikos Pelekis, Babis Theodoulidis, Ioannis Kopanak...
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
The process of resource distribution and load balance of a distributed P2P network can be described as the process of mining Supplement Frequent Patterns (SFPs) from query transact...
Yintian Liu, Yingming Liu, Tao Zeng, Kaikuo Xu, Ro...
The problem of automatically classifying the gender of a blog author has important applications in many commercial domains. Existing systems mainly use features such as words, wor...