Imbalanced data become an obstacle in data mining nowadays, minority class sometimes are more important than majority class, just like in medical diagnosis, credit card fraud and etc. This paper focuses on the imbalanced data problem that adaboost…
Big data plays a major role in the learning, manipulation, and forecasting of information intelligence. Due to the imbalance of data delivery, the learning and retrieval of information from such large datasets can result in limited classification…
Leaks represent one of the most relevant faults in water distribution networks (WDN), resulting in severe losses. Despite the growing research interest in critical infrastructure monitoring, most of the solutions present in the literature cannot…
The difficulty in classifying imbalanced datasets is one of the complexities preventing meaningful information from being extracted. It is common in the actual data applications for instances from a class of primary concern to be overshadowed by…
In Mobile Performance Marketing (MPM), monetary compensation only occurs when an advertisement results in a conversion (e.g., sale of a product or service). In this work, we propose an intelligent decision support system (IDSS) to automatically…
This paper presents an extension of a comparative study of classifier architectures for automatic fault diagnosis, with a special emphasis on the Extreme Learning Machine (ELM), with and without kernel mapping. Besides the explanation of the ELM…
This research focuses on how CO2 volume emission by producing electricity should be released suitably as well as how electricity is produced sufficiently for Thailand country at the same time. We used data mining: linear regression and classification…