In response to the rapid development of DNA Microarray technology, many classification methods have been used for Microarray classification. SVMs, decision trees, Bagging, Boostin...
Hong Hu, Jiuyong Li, Ashley W. Plank, Hua Wang, Gr...
Sequence mining is often conducted over static and temporal datasets as well as over collections of events (episodes). More recently, there has also been a focus on the mining of ...
Data mining is playing an important role in decision making for business activities and governmental administration. Since many organizations or their divisions do not possess the...
The support vector machine (SVM) is a wellestablished and accurate supervised learning method for the classification of data in various application fields. The statistical learnin...
This paper deals with studies the problem of identification and extraction of flat and nested data records from a given web page. With the explosive growth of information sources ...
The importance of predicting Web users' behaviour and their next movement has been recognised and discussed by many researchers lately. Association rules and Markov models ar...
If the dataset available to machine learning results from cluster sampling (e.g. patients from a sample of hospital wards), the usual cross-validation error rate estimate can lead...
The concept of older adults contributing to society in a meaningful way has been termed `active ageing'. We present applications of data mining techniques on the active agein...
The efficient market hypothesis states that an efficient market immediately incorporates all available information into the price of the traded entity. It is well established that...
This paper explores the size and value effect in influencing performance of individual companies using backpropagation neural networks. According to existing theory, companies wit...