Data mining and machine learning must confront the problem of pattern maintenance because data updating is a fundamental operation in data management. Most existing data-mining alg...
Classifying high-dimensional numerical data is a very challenging problem. In high dimensional feature spaces, the performance of supervised learning methods suffer from the curse...
Efficient and expressive comparison of sequences is an essential procedure for learning with sequential data. In this article we propose a generic framework for computation of sim...
We introduce CCASH (Cost-Conscious Annotation Supervised by Humans), an extensible web application framework for cost-efficient annotation. CCASH provides a framework in which cos...
Paul Felt, Owen Merkling, Marc Carmen, Eric K. Rin...
Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unse...