Description: Conditional Random Field（CRF）是重要的串学习模型，广泛用于自然语言处理的各个领域。CRF++是CRF的一个高效的实现，具有可扩展性好，功能强大的优点。-Conditional Random Field (CRF) is an important learning model series , widely used in natural language processing in various fields. CRF CRF is the realization of an efficient, with scalability, and powerful advantage. Platform: |
Size: 1104468 |
Author:王志强 |
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Description: Conditional Random Field（CRF）是重要的串学习模型，广泛用于自然语言处理的各个领域。CRF++是CRF的一个高效的实现，具有可扩展性好，功能强大的优点。-Conditional Random Field (CRF) is an important learning model series , widely used in natural language processing in various fields. CRF CRF is the realization of an efficient, with scalability, and powerful advantage. Platform: |
Size: 676723 |
Author:liangbo |
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Description: Conditional Random Field（CRF）是重要的串学习模型，广泛用于自然语言处理的各个领域。CRF++是CRF的一个高效的实现，具有可扩展性好，功能强大的优点。-Conditional Random Field (CRF) is an important learning model series , widely used in natural language processing in various fields. CRF CRF is the realization of an efficient, with scalability, and powerful advantage. Platform: |
Size: 1104896 |
Author:王志强 |
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Description: Conditional Random Field（CRF）是重要的串学习模型，广泛用于自然语言处理的各个领域。CRF++是CRF的一个高效的实现，具有可扩展性好，功能强大的优点。-Conditional Random Field (CRF) is an important learning model series , widely used in natural language processing in various fields. CRF CRF is the realization of an efficient, with scalability, and powerful advantage. Platform: |
Size: 676864 |
Author:liangbo |
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Description: Conditional Random Field（CRF）是重要的串学习模型，广泛用于自然语言处理的各个领域。CRF++是CRF的一个高效的实现，具有可扩展性好，功能强大的优点。 -Conditional Random Field (CRF) is an important string of learning model, widely used in natural language processing in various fields. CRF++ Is CRF realize an efficient, scalable, and powerful advantages. Platform: |
Size: 1084416 |
Author:willee |
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Description: 说明：
基于条件随机场模型的经典理论介绍，广泛应用于命名实体识别，实体关系识别领域。-Note: Based on Conditional Random Fields model describes the classical theory is widely used in named entity recognition, entity-relationship identification field. Platform: |
Size: 357376 |
Author:lihaifeng |
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Description: hmm, mem, crf简介
hmm：hidden markov model 隐马尔科夫模型
mem: maximum entropy model 最大熵模型
crf: conditional random field 条件随机场模型-hmm, mem, crf Profile hmm: hidden markov model mem: maximum entropy model model crf: conditional random field Platform: |
Size: 827392 |
Author:ly |
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Description: 条件随机域模型及在语言分析系统中的应用A conditional random field model and its application to language analysis system-A conditional random field model and its application to language analysis system Platform: |
Size: 311296 |
Author:pen2012 |
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Description: Many computer vision problems can be formulated
in a Bayesian framework based on Markov Random Fields
(MRF) or Conditional Random Fields (CRF). Platform: |
Size: 678912 |
Author:wafaa |
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Description: 中文分词，利用条件随机场进行分词，里面有VC6写的和VC8写的两种。-Chinese word segmentation using conditional random field segmentation, which VC6 and VC8 write two. Platform: |
Size: 2380800 |
Author:gongxinchen |
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Description: CRF++-0.53,条件随机场命名实体识别，0.53版本，顺利通过测试运行--0.53 CRF, conditional random field named entity recognition, 0.53 version, successfully passed the test run Platform: |
Size: 1265664 |
Author:liping |
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Description: 条件随机场CRF图像处理工具，可以直接拿来用，值得下载学习。(Conditional random field CRF image processing tool.It can be used directly, it is worth downloading study.) Platform: |
Size: 1544192 |
Author:yiling
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Description: 《统计学习方法》是计算机及其应用领域的一门重要的学科。《统计学习方法》全面系统地介绍了统计学习的主要方法，特别是监督学习方法，包括感知机、k近邻法、朴素贝叶斯法、决策树、逻辑斯谛回归与最大熵模型、支持向量机、提升方法、EM算法、隐马尔可夫模型和条件随机场等。除第1章概论和最后一章总结外，每章介绍一种方法。叙述从具体问题或实例入手，由浅入深，阐明思路，给出必要的数学推导，便于读者掌握统计学习方法的实质，学会运用。为满足读者进一步学习的需要，书中还介绍了一些相关研究，给出了少量习题，列出了主要参考文献。(Statistical learning method is an important subject in computer and its application field. "Statistical learning method" comprehensively and systematically introduces the main method of statistical learning, especially the supervised learning method, including perceptron, k nearest neighbor method, Naive Bayesian method, decision tree, logistic regression and the maximum entropy model, support vector machine, lifting method, EM algorithm, hidden Markov model and conditional random field etc.. In addition to the introduction of the first chapter and the last chapter, a method is introduced in each chapter.) Platform: |
Size: 17750016 |
Author:Somnus2018
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Search - conditional random field