搜索资源列表
sbp
- 用于手写体字符识别的BP神经网络算法,用C语言编写,需要用一定数据的进行训练,然后用三层网络进行识别,可以试一试.-for Handwritten Character Recognition BP neural network algorithm, using C language, need certain data for training, and then use the three-tier network identification, may try.
PFR199801.rar
- PFR人民日报标注语料，它是中文信息处理的重要训练样本,PFR marked the People' s Daily corpus, which is an important Chinese information processing training samples
CRF++-0.51
- 应用在自然语言识别等领域的机器训练,最新版本的条件随机场工具-Applications in natural language recognition in areas such as machine training, the latest version of the conditions with the Airport tools
POSTagger_Src
- 包含了词条及其词性标记，频度信息的词典 练语料的格式要求： 每个词以 / 分隔， / 后是该词的词性标记。词性标记后至少要有一个空格。一个句子的所有词必须在同一行中。击“开始词性标注”选取文本文件（一次可以选择多个）进行标注处理-Includes a term and its part of speech marks, the frequency of information and training Corpus dictionary format requirements: Each w
hmmfan
- 一个用于 词性标注的 HMM程序。 包含 训练和测试功能。-One for the HMM-speech tagging procedures. Includes training and testing.
xuz95
- 软件特点 1、本软件包含会计账务管理、固定资产管理、进销存管理、工资管理四大管理系统。 适用于2000人以下的中小企业，功能强大，实现对企业经营及资产的全面财务管理。 2、本软件最大限度简化及减少了人工操作。具有操作简便、所见即所得、工作效率高、 稳定性好、安全可靠、保密性强等优点。永续使用，不需维护！ 3、界面设计简约整洁，所见即所得,在页面中设有简要提示,业务人员无需任何培训即 可操作，使企业财务电子化管理变成用计算器一样简单。使用当月即可甩掉手
fluent
- fluent培训的一些资料，希望对大家有所帮助。内容比较丰富-fluent training, some of the information you want to help. Content rich
segment
- 基于n元语法的分词。先训练后，再通过前后向最大匹配初步分词，在通过2元语法来消岐。-Based on the n-gram sub-word. The first training and then through to the maximum matching before and after the initial word, in through a 2-gram to eliminate qi.
POStag
- 词性标注。首先根据预料库训练模型，然后用得到的模型对未标记词性的语句进行词性标注。-Part of Speech Tagging. First, according to the training model is expected to libraries, and then get the model right part of speech of the statement is not marked for POS Tagging.
wordmark
- 通过一个已经标号词性的训练集来得到训练数据，再根据训练数据对需要进行分词的数据进行分词，采用概率最高的分词情况为最后结果。-By a label the parts of speech training set training data to get the need segmentation data based on the training data segmentation with the highest probability of segmentation for the fin
CTB
- 中文分词和词性分析通用的训练集，含POS。-Chinese word segmentation and part of speech analysis of generic training set.
randomGen.py.tar
- 首先利用现有文本训练trigram模型，再用模型随机生成n个单词的文本-First, the use of existing training trigram model text, and then the model is randomly generated n-word text
maxent
- 运用最大熵对一个文本中的类进行训练模型，然后可用模型进行预测，结果返回类名，是机器学习语言的重要部分，支持汉字分类-Use of maximum entropy of a text in class training model, the model can then be used to predict the results returned class name is an important part of machine learning languages, support for
SentimentClassification
- 任务描述：本实验要求对文本的情感态度进行二元分类(P/N)。这首先要求通过读入训 练数据并学习来建立一个文本模型，然后通过这一模型来判断测试文本的情感态度，并且与 所持有的标签进行对比，从而得到对该模型的评价。-Task Descr iption: This experiment requires emotional attitude text will be binary classification (P/N). This requires training data by read
wiki_100
- 使用Wikipedia中文训练的100维词向量(100 dimensional word vectors used in Chinese training in Wikipedia)