Platform for sharing and evaluation of intelligent algorithms. Data mining data, experiments, datasets, performance analysis, data repository, challenges. Research and applications, prediction. Data mining and machine learning
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
This list is intended to introduce some of the tools of Bayesian statistics and machine learning that can be useful to computational research in cognitive science.
Short introduction to Vector Space Model (VSM) In information retrieval or text mining, the term frequency - inverse document frequency also called tf-idf, is
The aim of this project is to produce age-appropriate non-fiction books for children from birth to age 12. These books are richly illustrated with photographs, diagrams, sketches, and original drawings. Wikijunior books are produced by a worldwide community of writers, teachers, students, and young people all working together. The books present factual information that is verifiable. You are invited to join in and write, edit, and rewrite each module and book to improve its content. Our books are distributed free of charge under the terms of the Creative Commons Attribution-ShareAlike License.
Mloss is a community effort at producing reproducible research via open source software, open access to data and results, and open standards for interchange.
C. Kemp, и K. Ramamohanarao. Proceedings of the 6th European Conference on Principles
of Data Mining and Knowledge Discovery (PKDD 2002), стр. 263--274. Berlin, Springer, (2002)
L. Schmidt-Thieme. Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 27-30 November 2005, стр. 378-385. Houston, Texas, USA, IEEE Computer Society, (2005)