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Introductory survey and applications of machine learning methods

OpenStax
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  Introduction to logistic regression
0.1 Introduction
0.2 What is all this about?
0.3 Linear regression
0.4 Generalized linear model
0.5 Probabilistic interpretation
0.6 Minimizing the cost function
0.7 Applying logistic regression
0.8 Data generation
0.9 Classification
0.10 Conclusion
1   Optimizing logistic regression for a particle physics application
1.1 Motivation
1.2 Project goal
1.3 Prior work - phys 491 summer 2011
1.4 Features
1.5 Classifiers
1.6 Current work - elec 631 fall 2011
1.7 Cost matrix
1.8 Ratio of signal to background in training set
1.9 Results
1.10 Conclusion
1.11 Future work
1.12 References
1.13 Acknowledgments
1.14 Directions for using code

Source:  OpenStax, Introductory survey and applications of machine learning methods. OpenStax CNX. Dec 22, 2011 Download for free at http://legacy.cnx.org/content/col11400/1.1
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