Cost-sensitive classification problem (Poster)

T.G.K. Calders, M. Pechenizkiy

Research output: Contribution to conferencePoster

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In practical situations almost all classification problems are cost-sensitive or utility based one way or another. This exercise mimics a real situation in which students first have to translate a description into a datamining workflow, learn a prediction model, apply it to new data, and set up a testing strategy to estimate what will be the performance. The exercise is suitable for students following an introductory data mining course; it has been used in my introductory data mining class (3ECTS; 3rd BSc Computer Science students) for two years now. Students work on it in class for approximately 1 hour and finish the exercise at home. Solutions are to be sent to the lecturer and discussion the solutions the next lecture takes approximately 30 minutes.
Original languageEnglish
Publication statusPublished - 2012
Eventconference; Workshop on Teaching Machine Learning; 2012-06-30; 2012-06-30 -
Duration: 30 Jun 201230 Jun 2012


Conferenceconference; Workshop on Teaching Machine Learning; 2012-06-30; 2012-06-30
OtherWorkshop on Teaching Machine Learning

Bibliographical note

Workshop on Teaching Machine Learning (Edinburgh, Scotland, June 30, 2012; co-located with ICML 2012)


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