4 projects tagged "machine learning"
Updated 04 Jul 2011
K-tree
| Pop | 82.57 |
|---|---|
| Vit | 2.17 |
K-tree provides a scalable approach to clustering by combining the B+-tree and k-means algorithms. Clustering can be used to solve problems in signal processing, machine learning, and other contexts. It has recently been used to solve document clustering problems on the Wikipedia collection.
Updated 19 Aug 2009
x2search
| Pop | 21.93 |
|---|---|
| Vit | 1.00 |
x2search is a crawler based on machine learning algorithms that finds pages and documents that are similar to given positive and different to given negative examples. The learned classifiers can be exported and saved for later reuse. It features multiple settings for searching by domain/server, etc. and has a plug-in mechanism for adding document types to be searched.
Updated 30 Dec 2012
MyMediaLite
| Pop | 85.81 |
|---|---|
| Vit | 12.63 |
MyMediaLite is a lightweight, multi-purpose library of recommender system algorithms. It addresses the two most common scenarios in collaborative filtering: rating prediction (e.g. on a scale of 1 to 5 stars), and item prediction from implicit feedback (e.g. from clicks or purchase actions). It contains dozens of recommender engines, including state-of-the-art matrix factorization methods. It also supports real-time updates to the recommender engines, storing engines to disk and reloading them again, and several evaluation measures to compare the accuracy of different recommender system methods. Three command-line programs that offer most of the functionality contained in the library are included.
Updated 07 Nov 2011
pyuds
| Pop | 16.28 |
|---|---|
| Vit | 23.69 |
pyuds is a Python library for measuring uncertainty in the Dempster-Shafer theory of evidence. The functionals supported are the Generalized Hartley (GH) uncertainty functional, Generalized Shannon (GS) uncertainty functional, and Aggregate Uncertainty (AU) functional. The library can be utilized either through its API, or through a user-friendly Web interface.
