Alternatives and similar repositories for autoxgb

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

• cerlymarco / shap-hypetune
  A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
  ☆583Updated last year
• AutoViML / featurewiz
  Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshad…
  ☆676Updated 10 months ago
• aerdem4 / lofo-importance
  Leave One Feature Out Importance
  ☆854Updated 10 months ago
• Ekeany / Boruta-Shap
  A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.
  ☆641Updated last year
• AutoViML / Auto_TS
  Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ra…
  ☆765Updated last year
• linkedin / FastTreeSHAP
  Fast SHAP value computation for interpreting tree-based models
  ☆549Updated 2 years ago
• AutoViML / Auto_ViML
  Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upo…
  ☆545Updated 11 months ago
• ray-project / tune-sklearn
  A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.
  ☆469Updated 2 years ago
• arnabbiswas1 / kaggle_pipeline_tps_aug_22
  Kaggle Pipeline for tabular data competitions
  ☆205Updated last year
• predict-idlab / powershap
  A power-full Shapley feature selection method.
  ☆211Updated 2 months ago
• cod3licious / autofeat
  Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
  ☆535Updated last week
• StatMixedML / XGBoostLSS
  An extension of XGBoost to probabilistic modelling
  ☆679Updated 2 weeks ago
• alteryx / evalml
  EvalML is an AutoML library written in python.
  ☆836Updated 3 weeks ago
• rasgointelligence / feature-engineering-tutorials
  Data Science Feature Engineering and Selection Tutorials
  ☆290Updated 2 weeks ago
• tusharsarkar3 / XBNet
  Boosted neural network for tabular data
  ☆217Updated last year
• guillermo-navas-palencia / optbinning
  Optimal binning: monotonic binning with constraints. Support batch & stream optimal binning. Scorecard modelling and counterfactual expl…
  ☆506Updated last week
• mikekeith52 / scalecast
  The practitioner's forecasting library
  ☆347Updated last week
• pytorch-tabular / pytorch_tabular
  A standard framework for modelling Deep Learning Models for tabular data
  ☆1,615Updated last month
• baosenguo / Kaggle-MoA-2nd-Place-Solution
  ☆170Updated 5 years ago
• AnotherSamWilson / miceforest
  Multiple Imputation with LightGBM in Python
  ☆402Updated 2 months ago
• LocalCascadeEnsemble / LCE
  Random Forest or XGBoost? It is Time to Explore LCE
  ☆70Updated 2 years ago
• smazzanti / mrmr
  mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.
  ☆618Updated last year
• ryancheunggit / tabular_dae
  ☆53Updated 2 years ago
• ryancheunggit / Denoise-Transformer-AutoEncoder
  ☆349Updated 4 years ago
• ing-bank / probatus
  SHAP-based validation for linear and tree-based models. Applied to binary, multiclass and regression problems.
  ☆154Updated 8 months ago
• feature-engine / feature_engine
  Feature engineering package with sklearn like functionality
  ☆2,174Updated last month
• lmassaron / deep-learning-for-tabular-data
  An updated (2025) guide to Deep Learning for tabular data, comparing a fine-tuned Keras 3 (PyTorch backend) DNN and an Optuna-optimized…
  ☆47Updated 4 months ago
• loft-br / xgboost-survival-embeddings
  Improving XGBoost survival analysis with embeddings and debiased estimators
  ☆342Updated last year
• StatMixedML / LightGBMLSS
  An extension of LightGBM to probabilistic modelling
  ☆353Updated 2 weeks ago
• tunguz / TabularBenchmarks
  ☆203Updated 2 months ago