利用Map/Reduce的機器學習算法庫 Apache Mahout 0.6 發布
Mahout是一個利用Map/Reduce的機器學習算法庫，其思想源于斯坦福大學幾個學者在2006年的nips會議上發表的一篇文章“Map- Reduct for Machine Learning on Multicore"
Apache Mahout 0.6 發布了，建議所有開發者升級，該版本主要改進包括：
- 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
完整列表請看：release notes.
下載地址：Apache mirrors.
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