Apache Mahout 0.6 发布

摘要:Mahout是一个利用Map/Reduce的机器学习算法库，其思想源于斯坦福大学几个学者在2006年的nips会议上发表的一篇文章“Map- Reduct for Machine Learning on Multicore"...

　　Mahout是一个利用Map/Reduce的机器学习算法库，其思想源于斯坦福大学几个学者在2006年的nips会议上发表的一篇文章“Map- Reduct for Machine Learning on Multicore"

　　Apache Mahout 0.6 发布了，建议所有开发者升级，该版本主要改进包括：

　　Improved Decision Tree performance and added support for regression problems

　　New LDA implementation using Collapsed Variational Bayes 0th Derivative Approximation

　　Reduced runtime of LanczosSolver tests

　　K-Trusses, Top-Down and Bottom-Up clustering, Random Walk with Restarts implementation

　　Reduced runtime of dot product between vectors

　　Added MongoDB and Cassandra DataModel support

　　Increased efficiency of parallel ALS matrix factorization

　　SSVD enhancements

　　Performance improvements in RowSimilarityJob, TransposeJob

　　Added numerous clustering display examples

　　Many bug fixes, refactorings, and other small improvements

　　完整列表请看：release notes.

　　下载地址：Apache mirrors.