Alternatives and similar repositories for preprocessing

Users that are interested in preprocessing are comparing it to the libraries listed below

• weepon / feature_selection
  常用的特征选择方法
  ☆67Updated 3 years ago
• rogeroyer / feature_selection_GAAlgorithm
  基于遗传算法的特征选择
  ☆127Updated 6 years ago
• aflyingpig0226 / feature-engineering
  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
• jia-zhuang / xgboost-lightgbm-hyperparameter-tuning
  Bayesian Optimization and Grid Search for xgboost/lightgbm
  ☆79Updated 11 months ago
• luanshiyinyang / Stacking
  机器学习集成模型之Stacking各类模型及工具源码
  ☆120Updated 5 years ago
• rogeroyer / AI-challenger-contest
  马上AI全球挑战赛-违约用户风险预测 top2-solution
  ☆18Updated 7 years ago
• wikke / TimeSeriesPrediction
  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
  ☆56Updated 8 years ago
• loyalzc / transfer_learning
  Transfer Learning JDA and TrAdaboost
  ☆65Updated 7 years ago
• CcIsHandsome / -TOP1-
  CCF大数据与计算智能大赛-工件检测TOP1方案
  ☆28Updated 6 years ago
• yzkang / QH_FInSight
  国内首个迁移学习赛题 中国平安前海征信“好信杯”迁移学习大数据算法大赛 FInSight团队作品(算法方案排名第三)
  ☆86Updated 7 years ago
• luckyerdog / feature_select
  在sklearn下，几种常用的特征选择方法
  ☆41Updated 10 years ago
• fitzgerald0 / time_series_data_mining
  TensorFlow Probability；Time series model
  ☆127Updated 3 years ago
• syxiaa / RSMOTE
  Oversampling method based on relative density
  ☆13Updated 5 years ago
• felix-last / kmeans_smote
  Oversampling for imbalanced learning based on k-means and SMOTE
  ☆130Updated 4 years ago
• 634671436 / Air_Pollution_Forcast_Beijing
  基于Keras的LSTM多变量时间序列预测
  ☆185Updated 8 years ago
• yanhan19940405 / Data_machine_learning
  2019年CCF智能信用评分大赛个人源码库。包含XGboost模型调参，特征筛选，训练等方案。同时包含stacking模型融合方案
  ☆28Updated 5 years ago
• woairong / Xgboost-integration-model-based-on-moderate-greedy-parametric-strategy
  第三届“融360”天机智能算法挑战赛中“拒绝推断”赛题--复赛第四名的代码分享
  ☆11Updated 5 years ago
• zhulei227 / Stacking_Ensembles
  Stacking classification and regression
  ☆25Updated 6 years ago
• BackyardofAbela / EnsembleLearning
  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
• Albertsr / Class-Imbalance
  Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.
  ☆110Updated 5 years ago
• Designlotus / Anti-fraud-prediction-model
  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
  ☆43Updated 6 years ago
• massquantity / Class-Imbalance
  《机器学习之类别不平衡问题》文章代码
  ☆46Updated 7 years ago
• fuqiuai / sklearn-feature-engineering
  使用sklearn做特征工程
  ☆177Updated 7 years ago
• ideasplus / imbalance-learning
  There are some reproduced algorithms for learning from imbalanced data, including over-sampling,under-sampling and boosting
  ☆13Updated 2 years ago
• Nana0606 / student_and_teacher_classifier
  通过科研人员论文项目等数据，训练识别导师/学生的分类器。代码包括特征选择基础、网格搜索确定特征选择方法参数、不平衡数据的处理(oversampling、undersampling)和pu-learning方法在此问题上的应用
  ☆31Updated 6 years ago
• IceSuger / yancheng-sales
  天池-印象盐城-汽车销量预测大赛
  ☆36Updated 7 years ago
• upup123 / AAAI-2019-AFS
  The code of the AAAI-19 paper "AFS: An Attention-based mechanism for Supervised Feature Selection".
  ☆47Updated 6 years ago
• cainsmile / GA_for_Feature_Selection
  使用遗传算法结合决策树做特征选择/Using genetic algorithm for feature selection with decision tree
  ☆25Updated 7 years ago
• Hushengjing / Alitianchi-Guizhou-TravelTime-Prediction
  天池智慧交通预测挑战赛 - 比赛经历分享
  ☆15Updated 8 years ago
• EsmeYi / time-series-forcasting
  Using K-NN, SVM, Bayes, LSTM, and multi-variable LSTM models on time series forecasting
  ☆53Updated 6 years ago