ThinkingXuan / loan-risk-predictionLinks
💖基于机器学习的贷中风险预测模型--江苏银行“随e融”杯--二等奖💖
☆23Updated 3 years ago
Alternatives and similar repositories for loan-risk-prediction
Users that are interested in loan-risk-prediction are comparing it to the libraries listed below
Sorting:
- 机器学习的特征工程,包括特征抽取、特征预处理、特征选择、特征降维。☆25Updated 6 years ago
- 常用的特征选择方法☆68Updated 3 years ago
- 江苏银行“随e融”杯金融大数据建模挑战赛-一等奖☆9Updated 4 years ago
- 基于遗传算法的特征选择☆128Updated 5 years ago
- 现有聚类算法面向高维稀疏数据多未考虑类簇可重叠和离群点的存在,导致聚类效果不理想。针对此,提出一种可重叠子空间K-Means聚类算法(An Overlapping Subspace K-Means Clustering Algorithm, OS-K-Means)。给出类簇…☆30Updated 5 years ago
- 机器学习集成模型之Stacking各类模型及工具源码☆117Updated 4 years ago
- 数据预处理之缺失值处理,特征选择☆21Updated 6 years ago
- 包括决策树和随机森林进行离职人员预测,Xgboost和lightGBM的应用☆289Updated 5 years ago
- 基于ARIMA时间序列的销量预测模型,实际预测准确率达90%以上,内含有测试记录和实际上线效果。☆103Updated 5 years ago
- 2020 招商银行FinTech 数据赛道 rank10☆115Updated 5 years ago
- 基于KNN聚类算法结合Dynamic Time Warping(动态时间调整)的时间序列分类☆62Updated 6 years ago
- 智能风控 python金融风险管理与评分卡建模 数据和代码☆23Updated 3 years ago
- 马上AI全球挑战赛-违约用户风险预测 top2-solution☆19Updated 7 years ago
- Time Series Prediction, Stateful LSTM; 时间序列预测,洗发水销量/股票走势预测,有状态循环神经网络☆58Updated 7 years ago
- 交易欺诈作为信用卡行业面临的主要贷后风险业务问题,每年都使信用卡行业遭受巨额损失。基于大数据机器学习开发出高效的交易欺诈识别模型一直是金融行业的主要挑战之一。本次大赛以此作为主题☆44Updated 6 years ago
- 智能供应链分析,对顾客用rfm模型分类,用多种机器学习模型建模,进行欺诈订单预测,延迟发货预测,销售额预测,销售数量预测☆35Updated 4 years ago
- This is an implementation of the paper on "Improved K-means algorithm based on density Canopy".☆30Updated 6 years ago
- Community detection on Hollywood actors using various models: Louvain, Clauset-Newman-Moore, GCN, GraphSage, and GAT.☆10Updated 5 years ago
- Oversampling for imbalanced learning based on k-means and SMOTE☆128Updated 4 years ago
- 利用时间序列预测汽车销量☆41Updated 6 years ago
- 改进的k-prototypes聚类算法☆19Updated 4 years ago
- 在sklearn下,几种常用的特征选择方法☆40Updated 9 years ago
- 构建基于逻辑回归的评分卡模型☆45Updated 6 years ago
- 时间序列ARIMA模型的销量预测☆61Updated 7 years ago
- Bayesian Optimization and Grid Search for xgboost/lightgbm☆76Updated 5 months ago
- Stacking classification and regression☆25Updated 5 years ago
- 集成学习Stacking方法详解☆76Updated 5 years ago
- 2019科大讯飞工程机械赛题-亚军☆39Updated 5 years ago
- 基于Keras的LSTM多变量时间序列预测☆179Updated 7 years ago
- 本项目开发了一个机器学习和深度学习的训练工具。该训练工具基于sklearn和pytorch,不仅支持常规训练、交叉验证训练,还支持贝叶斯搜索参数,并可随时自动保存训练模型和日志。☆12Updated last year