- Mahout currently has Collaborative Filtering User and Item based recommenders K-Means, Fuzzy K-Means clustering Mean Shift clustering...Mahout currently has Collaborative Filtering User and Item based recommenders K-Means, Fuzzy K-Means clustering Mean Shift clustering Dirichlet process clustering Latent Dirichlet Allocation Singular value decomposition Parallel Frequent Pattern mining Complementary Naive Bayes classifier Random forest decision tree based classifier High performance java collections (previously colt collections) A vibrant community and many more cool stuff to come by this summer thanks to Google summer of code
- The Knowledge Discovery Machine Learning (KDML) group focuses on the neighboring subfields of computer science known as knowledge discovery in databases (K...The Knowledge Discovery Machine Learning (KDML) group focuses on the neighboring subfields of computer science known as knowledge discovery in databases (KDD, sometimes referred to simply as data mining) and machine learning (ML). For us, these fields include on the one hand the automated analysis of large data sets using intelligent algorithms that are capable of extracting from the collected data hidden knowledge in order to produce models that can be used for prediction and decision making. On the other hand, they also include algorithms and systems that are capable of learning from experience and adapting to their environment or their users.
- Workshop Proposal: March 09, 2009 Submission Deadline: April 15, 2009 Authors Notification: June 01, 2009 Final Manuscript Due: June 15, 2009...Workshop Proposal: March 09, 2009 Submission Deadline: April 15, 2009 Authors Notification: June 01, 2009 Final Manuscript Due: June 15, 2009
- This year's discovery challenge presents two tasks in the new area of social bookmarking. One task covers spam detection and the other covers tag ...This year's discovery challenge presents two tasks in the new area of social bookmarking. One task covers spam detection and the other covers tag recommendations. As we are hosting the social bookmark and publication sharing system BibSonomy, we are able to provide a dataset of BibSonomy for the challenge. A training dataset for both tasks is provided at the beginning of the competition. The test dataset will be released 48 hours before the final deadline. Due to a very tight schedule we cannot grant any deadline extension. The presentation of the results will take place at the ECML/PKDD workshop where the top teams are invited to present their approaches and results.
- @inproceedings{cone2006, author = {Sei-Hyung Lee and Karen M. Daniels}, Booktitle = {Proceedings of 6th SIAM Conference on Data Mining}, Dat...@inproceedings{cone2006, author = {Sei-Hyung Lee and Karen M. Daniels}, Booktitle = {Proceedings of 6th SIAM Conference on Data Mining}, Date-Added = {2007-04-29 16:58:13 +0200}, Date-Modified = {2007-06-19 18:52:22 +0200}, Keywords = {SVM, clustering}, Month = {May}, Pages = {484–488}, Title = {Cone Cluster Labeling for Support Vector Clustering}, Url = {http://www.siam.org/meetings/sdm06/proceedings/046lees.pdf}, Year = {2006}, Bdsk-File-1 = {YnBsaXN0MDDUAQIDBAUGBwpZJGFyY2hpdmVyWCR2ZXJzaW9uVCR0b3BYJG9iamVjdHNfEA9OU0tleWVkQXJjaGl2ZXISAAGGoNEICVRyb290gAGoCwwXGBkaHiVVJG51bGzTDQ4PEBMWWk5TLm9iamVjdHNXTlMua2V5c1YkY2xhc3OiERKABIAFohQVgAKAA4AHXHJlbGF0aXZlUGF0aFlhbGlhc0RhdGFfEEsuLi8uLi8uLi9QYXBlcnMvTGVlL0NvbmUgQ2×1c3RlciBMYWJlbGluZyBmb3IgU3VwcG9ydCBWZWN0b3IgQ2×1c3RlcmluZy5wZGbSGw8cHVdOUy5kYXRhTxECLgAAAAACLgACAAAJRG9jdW1lbnRzAAAAAAAAAAAAAAAAAAAAAAAAvs54rkgrAAAANyVBH0NvbmUgQ2×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}, Bdsk-Url-1 = {http://www.siam.org/meetings/sdm06/proceedings/046lees.pdf} }
- Each week a new paper is discussed, seems to be mostly in the domain of knowledge discovery, text mining machine learning
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