Machine Learning Meetup Notes: 2010-04-28: Difference between revisions
Jump to navigation
Jump to search
Mschachter (talk | contribs) (Created page with '*Mike S presented a mathematical overview of SVMs **Started with introduction to linear classification [http://en.wikipedia.org/wiki/Linear_classifier] **Discussed the kernel tri…') |
Mschachter (talk | contribs) No edit summary |
||
| Line 5: | Line 5: | ||
**Emphasized two important aspects of SVMs: | **Emphasized two important aspects of SVMs: | ||
***Dual problem is a quadratic programming problem that is easier to solve than the primal problem | ***Dual problem is a quadratic programming problem that is easier to solve than the primal problem | ||
***After dual problem is optimized, only the support vectors (the data points whose langrangian multipliers are > 0) are needed to make predictions for new data | ***After dual problem is optimized, only the support vectors (the data points whose langrangian multipliers are > 0) are needed to make predictions for new data (and their associated multipliers) | ||
*Thomas talked about the KDD conference and their data competition [https://pslcdatashop.web.cmu.edu/KDDCup/rules_data_format.jsp | |||
] | |||
*Sai skyped in and talked a bit about his use of libSVM for classification of user history on his website cssfingerprint.com | |||
*We talked a little bit about libSVM [http://www.csie.ntu.edu.tw/~cjlin/libsvm/] | |||
Revision as of 09:13, 29 April 2010
- Mike S presented a mathematical overview of SVMs
- Started with introduction to linear classification [1]
- Discussed the kernel trick [2]
- Loosely derived the loss function and dual loss function for support vector machines [3]
- Emphasized two important aspects of SVMs:
- Dual problem is a quadratic programming problem that is easier to solve than the primal problem
- After dual problem is optimized, only the support vectors (the data points whose langrangian multipliers are > 0) are needed to make predictions for new data (and their associated multipliers)
- Thomas talked about the KDD conference and their data competition [https://pslcdatashop.web.cmu.edu/KDDCup/rules_data_format.jsp
]
- Sai skyped in and talked a bit about his use of libSVM for classification of user history on his website cssfingerprint.com
- We talked a little bit about libSVM [4]