PPTChapter06
Learning On The Border:Active Learning in Imbalanced classification Data
Using support vector machine with a hybrid feature selection method to the stock trend prediction
h2oensemble with Erin Ledell at useR! Aalborg
A Brief Introduction to Linear Regression
Introduction to Supervised Machine Learning Concepts PRESENTED BY B. Barla Cambazoglu February 21, 2014.
Ch 6. Kernel Methods Pattern Recognition and Machine Learning, C. M. Bishop, 2006. Summarized by J. S. Kim Biointelligence Laboratory, Seoul National University.
Chapter 11 Analysis and Explanation. Chapter 11 Outline Explain how CI systems do what they do Only a few methodologies are discussed here Sensitivity.
Using Analytic QP and Sparseness to Speed Training of Support Vector Machines
Recall , in linear methods for classification and regression
Minimum Rank Error Language Modeling
Ch 6. Kernel Methods by Aizerman et al. (1964). Re-introduced in the context of large margin classifiers by Boser et al. (1992). Vapnik (1995), Burges.
