Applying Supervised Learning to Real-World Problems

Dragos D. Margineantu, Oregon State University

The last years have seen machine learning methods applied to an increasing variety of application problems such as: language, handwriting and speech processing, document classification, knowledge discovery in databases, industrial process control and diagnosis, fraud and intrusion detection, image analysis and many others. Our work starts from the realization that most of these problems require significant reformulation before learning algorithms can be applied, and in many cases, existing algorithms require modifications before being applied to a problem.


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