开始 Mahout
Mahout has prepared a bunch of examples and tutorials for users to quickly learn how to use its machine learning algorithms.
Mahout 支持的算法
| Mahout 0.12.0 Features by Engine¶ | |||||
| Single Machine | MapReduce | Spark | H2O | Flink | |
| Mahout Math-Scala Core Library and Scala DSL | |||||
| Mahout Distributed BLAS. Distributed Row Matrix API with R and Matlab like operators. Distributed ALS, SPCA, SSVD, thin-QR. Similarity Analysis. | x | x | x | ||
| Mahout Interactive Shell | |||||
| Interactive REPL shell for Spark optimized Mahout DSL | x | ||||
| Collaborative Filtering with CLI drivers | |||||
| User-Based Collaborative Filtering | 弃用 | 弃用 | x | ||
| Item-Based Collaborative Filtering | x | x | x | ||
| Matrix Factorization with ALS | x | x | |||
| Matrix Factorization with ALS on Implicit Feedback | x | x | |||
| Weighted Matrix Factorization, SVD++ | x | ||||
| Classification with CLI drivers | |||||
| Logistic Regression - trained via SGD | 弃用 | ||||
| Naive Bayes / Complementary Naive Bayes | 弃用 | x | |||
| Hidden Markov Models | 弃用 | ||||
| Clustering with CLI drivers | |||||
| Canopy Clustering | 弃用 | 弃用 | |||
| k-Means Clustering | 弃用 | 弃用 | |||
| Fuzzy k-Means | 弃用 | 弃用 | |||
| Streaming k-Means | 弃用 | 弃用 | |||
| Spectral Clustering | 弃用 | ||||
| Dimensionality Reduction note: most scala-based dimensionality reduction algorithms are available through the Mahout Math-Scala Core Library for all engines | |||||
| Singular Value Decomposition | 弃用 | 弃用 | x | x | x |
| Lanczos Algorithm | 弃用 | 弃用 | |||
| Stochastic SVD | 弃用 | 弃用 | x | x | x |
| PCA (via Stochastic SVD) | 弃用 | 弃用 | x | x | x |
| QR Decomposition | 弃用 | 弃用 | x | x | x |
| Topic Models | |||||
| Latent Dirichlet Allocation | 弃用 | 弃用 | |||
| Miscellaneous | |||||
| RowSimilarityJob | 弃用 | x | |||
| Collocations | 弃用 | ||||
| Sparse TF-IDF Vectors from Text | 弃用 | ||||
| XML Parsing | 弃用 | ||||
| Email Archive Parsing | 弃用 | ||||
| Evolutionary Processes | x |
说明
