Location:
Search - CRFsuite
Search list
Description: CRFsuite is a very fast implmentation of the Conditional Random Fields (CRF) algorithm. It handles tens of thousands sentences in merely one second.
In comparison to CRF++, CRFSuite yields substantially better efficiency performance
Platform: |
Size: 445440 |
Author: Yu-Chieh Wu |
Hits:
Description: CRF最新java版软件，包含说明文档，由印度工作组负责开发-CRF latest java version of the software, including documentation, by the working group responsible for the development of India
Platform: |
Size: 32768 |
Author: swling |
Hits:
Description: CRFsuite: a fast implementation of Conditional Random Fields (CRFs)
CRFSuite is an implementation of Conditional Random Fields (CRFs) for labeling sequential data. The first priority of this software is to train and use CRF models as fast as possible even at the expense of its memory space and code generality. CRFsuite runs 5.4 - 61.8 times faster than C++ implementations for training. CRFsuite supports parameter estimation with L1 regularization (Laplacian prior) using Orthant-Wise Limited-memory Quasi-Newton (OW-LQN) method and L2 regularization (Gaussian prior) using Limited-memory BFGS (L-BFGS) method.,CRFsuite: a fast implementation of Conditional Random Fields (CRFs)
CRFSuite is an implementation of Conditional Random Fields (CRFs) for labeling sequential data. The first priority of this software is to train and use CRF models as fast as possible even at the expense of its memory space and code generality. CRFsuite runs 5.4- 61.8 times faster than C++ implementations for training. CRFsuite supports parameter estimation with L1 regularization (Laplacian prior) using Orthant-Wise Limited-memory Quasi-Newton (OW-LQN) method and L2 regularization (Gaussian prior) using Limited-memory BFGS (L-BFGS) method.
Platform: |
Size: 29696 |
Author: icypriest |
Hits:
Description: CRFsuite: a fast implementation of Conditional Random Fields (CRFs)
CRFSuite is an implementation of Conditional Random Fields (CRFs) for labeling sequential data. The first priority of this software is to train and use CRF models as fast as possible even at the expense of its memory space and code generality. CRFsuite runs 5.4 - 61.8 times faster than C++ implementations for training. CRFsuite supports parameter estimation with L1 regularization (Laplacian prior) using Orthant-Wise Limited-memory Quasi-Newton (OW-LQN) method and L2 regularization (Gaussian prior) using Limited-memory BFGS (L-BFGS) method.,CRFsuite: a fast implementation of Conditional Random Fields (CRFs)
CRFSuite is an implementation of Conditional Random Fields (CRFs) for labeling sequential data. The first priority of this software is to train and use CRF models as fast as possible even at the expense of its memory space and code generality. CRFsuite runs 5.4- 61.8 times faster than C++ implementations for training. CRFsuite supports parameter estimation with L1 regularization (Laplacian prior) using Orthant-Wise Limited-memory Quasi-Newton (OW-LQN) method and L2 regularization (Gaussian prior) using Limited-memory BFGS (L-BFGS) method.
Platform: |
Size: 1804288 |
Author: icypriest |
Hits: