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Machine Learning Techniques for Data Mining

Topics in Artificial Intelligence:. Machine Learning Techniques for Data Mining. B Semester 2000 Lecturer: Eibe Frank. Simplicity first. Simple algorithms often work surprisingly well Many different kinds of simple structure exist: One attribute might do all the work

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370 views • 35 slides

Evaluation

Evaluation. Evaluation. How predictive is the model we learned? Error on the training data is not a good indicator of performance on future data Simple solution that can be used if lots of (labeled) data is available: Split data into training and test set

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328 views • 30 slides

Geoffrey Hinton

CSC321: 2011 Introduction to Neural Networks and Machine Learning Lecture 9: Ways of speeding up the learning and preventing overfitting. Geoffrey Hinton. Five ways to speed up learning. Use an adaptive global learning rate Increase the rate slowly if its not diverging

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307 views • 17 slides

Machine Learning CSE 681

Machine Learning CSE 681. CH2 - Supervised Learning Model Assesment. Model Assesment. We can measure the generalization ability ( performance) of a hypothesis, namely, the quality of its inductive bias, if we have access to data outside the training set.

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333 views • 16 slides

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Machine Learning Techniques for Data Mining

Evaluation

Geoffrey Hinton

Machine Learning CSE 681