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The top documents tagged [features x1]
A Guideline to Statistical and Machine Learning
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Automated Parameter Setting Based on Runtime Prediction:
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580.691 Learning Theory Reza Shadmehr Linear and quadratic decision boundaries Kernel estimates of density Missing data
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Naïve Bayes Classification
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Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms
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Naïve Bayes Classification Material borrowed from Jonathan Huang and I. H. Witten’s and E. Frank’s “Data Mining” and Jeremy Wyatt and others
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Automated Parameter Setting Based on Runtime Prediction:
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Motivation: Why automatic parameter tuning ? (1)
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Feature Selection with Branch and Bound
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Lectures 17,18 – Boosting and Additive Trees Rice ECE697 Farinaz Koushanfar Fall 2006
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