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Fujitsu Laboratories Ltd. today announced the development of a machine-learning technology that can generate highly accurate predictive models from datasets of more than 50 million records in a matter of hours.
Current techniques for generating highly accurate predictive models need to examine every combination of learning algorithm and configuration, taking more than one week to learn from a dataset containing 50 million records.
Fujitsu Laboratories has now developed a technology that estimates machine-learning results from a small set of sample data and the accuracy of past predictive models, extracts the learning algorithm and configuration combination that produce the most accurate result, and applies it to the larger dataset. This results in highly accurate predictive models from datasets of 50 million records in a few hours.
Predictive models produced by this technology can work to quickly make improvements, such as minimizing membership cancellations on e-commerce websites and enhancing response times to equipment failures.
Details of this technology are being presented at the meeting of the Information-Based Induction Sciences and Machine Learning (ISIMBL), opening Monday, September 14 at Ehime University in Japan.

 

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