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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。

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.

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)。

arima-plot-of-residuals

使用AIC准则进行参数选择，之后采用ARIMA模型进行时间序列预测，最后给出残差图。The AIC criterion is used to select the parameters, and then ARIMA model is used to predict the time series. Finally, the residual diagram is given.

bayesian-computation-with-r-solutions

Part of the solutions about 《Bayesian Computation with R》(Jim Albert)

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

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.

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。

chinese-sentiment-analysis-and-lda-topic

使用中文情感词汇本体库进行情感分析，之后对每种情感的文本进行主题分析。Using Chinese Sentiment Dictionary for Sensitive Analysis, Then applying LDA Topic Analysis for each Emotion.

comment-sentiment-analysis

使用基于情感词典的情感分析方法对评论信息进行情感分析。The Sentiment Analysis Method based on Sentiment Dictionary is used for Comment Information.

credit-data-analysis

实现对信贷数据的数据预处理，数据分析。之后利用多种分类算法对公司是否违约进行预测。Realize the data preprocessing and data analysis of credit data. Then, it uses a variety of classification algorithms to predict whether the company defaults.

cvpr-2020-leap

Unofficial implement of LEAP(Deep Representation Learning on Long-tailed Data: A Learnable Embedding Augmentation Perspective) for Multi-Label Classification.

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.

gmm-kmeans-for-outlier-detection

针对一维时间序列数据，采用GMM和K-Means算法进行异常点检测。For one-dimensional time series data, GMM and K-means algorithm are used to detect outliers.

grey-model

使用灰色系统理论做负荷预测。Using Grey System Theory to Make Load Forecasting

housing-price-prediction

Using 5 models(lasso,elastic net,KernelRidge, boosting, xgboost) to predict the housing price

ilaco

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.

lda-for-chinese-topic-generation

使用LDA模型进行中文文本的主题生成。Using LDA Model for Chinese Topic Generation.

lda-gensim

使用LDA模型提取n个句子的主题，并统计每个主题出现的频次。LDA model is used to extract the topic of N sentences, and the frequency of each topic is counted.

leetcode

My practice of LeetCode.

linear-regression

Using linear regression to predict sales volume

logistic-regression

Using logistic regression to predict bear market probability

logistic-regression-variable-selection

使用logistic回归预测违约事件，实现变量选择。

lsfa

The code for our paper "Label-Specific Feature Augmentation for Long-Tailed Multi-Label Text Classification”

lstm-classification

使用LSTM解决分类问题。Using LSTM to solve classification problems.

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.

lstm-stock-predict

Using LSTM to forecast stock return

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.