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Learning from imbalanced data sets is a hot and challenging research topic with many real world applications. Many studies have been conducted on integrating sampling-based techniques and ensemble learning for imbalanced data sets. However, most existing sampling methods suffer from the problems of information loss, over-fitting, and additional bias. Moreover, there is no single model that can be...
With decades of investments, productivity has still continued to be a major issue for many digital circuit designers. One of the most important factors in improving productivity is design reuse, which current tools have yet to fully exploit. Reusing designs involve manually searching through repositories to find a design that meets the requirements of a project. This search can be tedious and often...
This paper describes a real-time information integration and analytics system called InXite for multi-purpose applications. InXite is designed to detect evolving patterns and trends in streaming data including social media data (e.g., tweets). InXite comprises of multiple modules including InXite Registration and Dashboard, InXite Real-time Data Streamer, InXite Information Integrator and InXite Analytics...
Choosing and implementing technologies to extract value from big data are constant challenges for business and governments alike. This paper describes the design and implementation of a data mining tool to analyze the XML data of the U.S. university campus crimes. The main aim of this tool is to extract data stored in XML documents and to provide summarized information that can help students in determining...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.