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用LSTM进行文本的情感分析
A curated list of awesome imbalanced learning papers, codes, frameworks, and libraries. | 类别不平衡学习:论文、代码、框架与库
This is a set of matlab code for building a BPNN optimized by GA
使用bp神经网络预测电力负荷,使用小型数据集,通过一个简单的例子。Using BPNN to predict power load, using small data set, a simple example.
基于Python的申请信用评分卡模型分析
Machine learning model for predicting credit default
(已完结)《极客时间数据分析实战45讲-详细笔记》包含markdown、图片、思维导图、代码 、数据。 可直接阅读代码、测试!
Real-time emotion recognition using convolutional neural nets.
微博情感分析
针对手机评论数据的情感挖掘与分析项目,基于依存句法分析和情感词库提取特征词,并对特征词做情感极性预测标注。
python 用GA算法优化BP神经网络
Implementation of Genetic Algorithm for feature selection of neural networks proposed by Genetic algorithm-based heuristic for feature selection in credit risk assessment paper.
⚡️⚡️⚡️《机器学习实战》代码(基于Python3)🚀
Exercises answers to the book "machine-learning" written by Prof. Zhou Zhihua of Nanjing University
This repository contains the source code for four oversampling methods that I wrote in MATLAB: 1) SMOTE 2) Borderline SMOTE 3) Safe Level SMOTE 4) ASUWO (Adaptive Semi-Unsupervised Weighted Oversampling)
The "Python Machine Learning (2nd edition)" book code repository and info resource
Social Context Analysis aNd Emotion Recognition
新浪微博情感分析应用
speech emotion recognition using a convolutional recurrent networks based on IEMOCAP
手写实现李航《统计学习方法》书中全部算法
代码主要包括:1。特征提取 首先对文本信息进行分词处理,采用基于字符串匹配的方法: 假如一段叫:李二狗就是一个** 基于匹配的方法就是依次截取一到多个词,并与字典库进行匹配。如二狗,如果匹配到字典中有这个词,则将其分为一个词;当取到“狗就”,发现字典中没有与之匹配的,则说明这个不是一个词语,进行顺序操作,最优将这段话分为:李 二狗 就是 一个 **。 2. 得到分词后的文本之后,就是转换成数字编码,因此电脑没办法识别汉字。这一部分叫特征表示,即用数字的方式表示中文文本,采用的方法是基于词带模型的特征表示: 词带就是字典--程序中那个dictionary.mat。我们将分词处理之后的文本中的每一个词语,分别与字典中的词进行匹配,只要出现过就为1,否则为0。 如 字典中的词含有:李 周 吴 郑 王 他妈的 就是 大 ** 一个 三炮 也是 瓜娃子,一共13词(当然正常的词典都是上万个词),将1中得到的词语与之匹配,则李二狗就是一个**对应的数字编码就应该是 1 0 0 0 0 0 1 0 1 1 0 0 0 3,通过2我们将文本表示成了数字,但是这样的表示通常都是稀疏的(因为一般字典都含有上万个词,所以得到的数字表示大部分都是0),为此我们利用降维方法,消除掉这些冗余特征。这里我们采用的PCA(主成分分析)进行降维,并降至15维。 4. 文本分类,采用的就是bp网络 代码修改的地方不多,主要就是超参数的选择,(1)如pca的降维数,维数过高,包含冗余数据,过低又会删除掉重要信息。(2)bp网络结构的调整,如隐含层节点数,学习率,等
Models for predicting emotions from English tweets.
emotion classfician
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JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
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A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
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Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.