Pinned Repositories
Air-Quality-Prediction
2021年研究生数学建模竞赛B题,全国二等奖,空气质量预报二次建模,时间序列数据分析与回归预测。Time Series Prediction&Air Quality Prediction.
BP-RBF-Prediction
使用BP神经网络、RBF神经网络以及PSO优化的RBF神经网络进行数据的预测
CVPR-2020-LEAP
Unofficial implement of LEAP(Deep Representation Learning on Long-tailed Data: A Learnable Embedding Augmentation Perspective) for Multi-Label Classification.
Matrix-Factorization-for-Recommendation
Using Matrix Factorization/Probabilistic Matrix Factorization to solve Recommendation。矩阵分解进行推荐系统算法。
Matrix-Factorization-Implicit-Feedback
使用矩阵分解算法处理隐式反馈数据,并进行Top-N推荐。The matrix factorization algorithm is used to process the implicit feedback data and make top-N recommendation.
multi-factor-strategy-joinquant
在聚宽(joinquant)平台上使用多因子策略进行量化投资模拟。
NCF-MF-for-Recommendation
分别使用传统方法(KNN,SVD,NMF等)和深度方法(NCF)进行推荐系统的评分预测。Traditional methods (KNN, SVD, NMF, etc.) and depth method (NCF) were used to predict rating of the recommendation system.
P300-BCI-Data-Analysis
2020年研究生数学建模竞赛C题,全国二等奖,分析脑机接口数据进行分析预测。The data of BCI were analyzed and predicted.
PSO-RBF-NN
使用粒子群算法优化的RBF神经网络进行预测。RBF neural network optimized by particle swarm optimization is used for prediction.
RBF-BP-MATLAB
使用RBF、BP神经网络进行预测。RBF/BP neural network is used for prediction.
stxupengyu's Repositories
stxupengyu/BP-RBF-Prediction
使用BP神经网络、RBF神经网络以及PSO优化的RBF神经网络进行数据的预测
stxupengyu/PSO-RBF-NN
使用粒子群算法优化的RBF神经网络进行预测。RBF neural network optimized by particle swarm optimization is used for prediction.
stxupengyu/RBF-BP-MATLAB
使用RBF、BP神经网络进行预测。RBF/BP neural network is used for prediction.
stxupengyu/Stochastic-Process-Ross-2nd-edition
Here is the exercise solution of stochastic process Ross 2nd Edition collected by the author. The answers are from the stochastic process courses of Umich, Columbia University and BJTU respectively. Due to the different assignments assigned by each teacher, the answers provided by each university are not complete, for your comprehensive reference.
stxupengyu/BPNN-MATLAB
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.
stxupengyu/LSTM-regression-and-classification
使用LSTM对股票价格进行回归预测,对股价涨跌进行分类预测。We use LSTM to forecast the stock price and classify the rise and fall of the stock price.
stxupengyu/time-series-analysis
使用经典的AR、MA、ARMA、ARIMA、ARCH、GARCH时间序列模型进行模型的检验和拟合。The classic AR, MA, ARMA, ARIMA, ARCH, GARCH time series models are used to test and predict the model.
stxupengyu/Grey-Model
使用灰色系统理论做负荷预测。Using Grey System Theory to Make Load Forecasting
stxupengyu/Econometrics-Example
计量经济学的实例分析包括多元回归分析,多重共线性,对数回归,虚拟变量分段线性回归,多项式拟合以及时间序列。The case analysis of econometrics includes multiple regression analysis, multicollinearity, logarithm regression, piecewise linear regression of dummy variable, polynomial fitting and time series.
stxupengyu/imbalanced-classification
根据60个特征,70万条数据预测5G用户,一个典型的不平衡二分类问题。According to 60 features, 700000 pieces of data predict 5G users, a typical imbalance problem.
stxupengyu/SVM-RFE
SVM classification, RFE feature selection
stxupengyu/SARIMA
使用SARIMA模型进行时间序列预测。Time series prediction using SARIMA model.
stxupengyu/maximum-likelihood-estimation
介绍和举例(正态分布、泊松分布、伽马分布)展示了极大似然估计。This paper introduces and gives examples (normal distribution, Poisson distribution, gamma distribution) to show the MLE.
stxupengyu/lstm-classification
使用LSTM解决分类问题。Using LSTM to solve classification problems.
stxupengyu/Matrix-Factorization-for-Recommendation
Using Matrix Factorization/Probabilistic Matrix Factorization to solve Recommendation。矩阵分解进行推荐系统算法。
stxupengyu/sparse-convex-clustering-demonstration
R语言包“稀疏凸聚类(scvxclustr)”的实验演示。Experimental demonstration of R package: "sparse-convex-clustering(scvxclustr)".
stxupengyu/Bayesian-Computation-with-R-Solutions
Part of the solutions about 《Bayesian Computation with R》(Jim Albert)
stxupengyu/BPNN-R
Using back propagation neural network(BPNN) to forecasting the price. 使用R语言实现BP神经网络回归预测。
stxupengyu/Housing-Price-Prediction
Using 5 models(lasso,elastic net,KernelRidge, boosting, xgboost) to predict the housing price
stxupengyu/logistic-regression-variable-selection
使用logistic回归预测违约事件,实现变量选择。
stxupengyu/XML-data-processing
处理多个微博上爬取的XML数据,转换为pandas.dataframe格式。Process XML data crawled from multiple microblogs and convert it to pandas.dataframe format.
stxupengyu/XML-to-DataFrame
将XML通过ElementTree转化为numpy/DataFrame格式。通过一个简单的例子。XML to Numpy/Pandas, a simply example.
stxupengyu/2003-SARS-stock-price-analysis
将2003年非典(SARS)时期的**股市数据与对应事件放在股价变化图上,进行分析。
stxupengyu/ARIMA
Time series prediction with ARIMA, to predict the price. A simple example. 使用ARIMA对价格序列进行预测(R语言)。
stxupengyu/LeetCode
My practice of LeetCode.
stxupengyu/linear-regression
Using linear regression to predict sales volume
stxupengyu/logistic-regression
Using logistic regression to predict bear market probability
stxupengyu/NLP-Preprocessing
实现英文自然语言处理的预处理功能, 处理网页爬取的NLP数据. To deal with the XML data, and implement the NLP preprocessing function.
stxupengyu/stock-price-predict
Using linear regression/artificial neural network(ANN)/long short term memory(LSTM) to predict stcok price
stxupengyu/time-series-predict
Using Holt-Winters, ARIMA and SARIMA model to predict the electricity consumption