A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
☆584Jun 8, 2024Updated 2 years ago
Alternatives and similar repositories for shap-hypetune
Users that are interested in shap-hypetune are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.☆657Feb 19, 2024Updated 2 years ago
- Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshad…☆683Feb 19, 2025Updated last year
- All Relevant Feature Selection☆145Apr 3, 2025Updated last year
- A power-full Shapley feature selection method.☆215Oct 7, 2025Updated 11 months ago
- A python package for time series forecasting with scikit-learn estimators.☆163Apr 4, 2024Updated 2 years ago
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- Feature engineering and selection open-source Python library compatible with sklearn.☆2,281Sep 19, 2026Updated last week
- Fast SHAP value computation for interpreting tree-based models☆566Jun 26, 2023Updated 3 years ago
- SHAP-based validation for linear and tree-based models. Applied to binary, multiclass and regression problems.☆154Sep 8, 2026Updated 2 weeks ago
- Linear Prediction Model with Automated Feature Engineering and Selection Capabilities☆547Jan 6, 2026Updated 8 months ago
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,621Updated this week
- nannyml: post-deployment data science in python☆2,156Jul 12, 2025Updated last year
- Python implementations of the Boruta all-relevant feature selection method.☆1,628Nov 13, 2025Updated 10 months ago
- 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models☆3,259Updated this week
- An extension of XGBoost to probabilistic modelling☆728Aug 14, 2026Updated last month
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- Forecasting with Gradient Boosted Time Series Decomposition☆198Jan 11, 2026Updated 8 months ago
- A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.☆1,596Updated this week
- Hierarchical Time Series Forecasting with a familiar API☆225May 12, 2023Updated 3 years ago
- Natural Gradient Boosting for Probabilistic Prediction☆1,889Sep 2, 2026Updated 3 weeks ago
- A python library to build Model Trees with Linear Models at the leaves.☆388Jul 19, 2024Updated 2 years ago
- An extension of LightGBM to probabilistic modelling☆397Aug 14, 2026Updated last month
- Predictive Power Score (PPS) in Python☆1,171Mar 11, 2026Updated 6 months ago
- Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upo…☆548Jan 30, 2025Updated last year
- A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.☆2,077May 22, 2026Updated 4 months ago
- Managed Database hosting by DigitalOcean • AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- Scalable machine 🤖 learning for time series forecasting.☆1,282Updated this week
- Leave One Feature Out Importance☆872Feb 14, 2025Updated last year
- mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.☆630Nov 19, 2024Updated last year
- Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.☆2,512Feb 11, 2026Updated 7 months ago
- Lightning ⚡️ fast forecasting with statistical and econometric models.☆4,916Updated this week
- Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.☆761Updated this week
- Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML va…☆4,056Dec 28, 2025Updated 9 months ago
- EvalML is an AutoML library written in python.☆850Jan 14, 2026Updated 8 months ago
- Lightweight Python package for generating classification intervals in binary classification tasks using Pearson residuals and conformal p…☆26Feb 20, 2026Updated 7 months ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- APDTFlow is a modern and extensible forecasting framework for time series data that leverages advanced techniques including neural ordina…☆45Jun 14, 2026Updated 3 months ago
- An unsupervised feature selection technique using supervised algorithms such as XGBoost☆92Jan 6, 2024Updated 2 years ago
- Feature selection package based on SHAP and target permutation, for pandas and Spark☆31Mar 1, 2022Updated 4 years ago
- Probabilistic prediction with XGBoost.☆119Mar 22, 2025Updated last year
- An open-source AutoML Library based on PyTorch☆306Sep 3, 2026Updated 3 weeks ago
- A game theoretic approach to explain the output of any machine learning model.☆25,783Updated this week
- Feature selection library in python☆148Jul 21, 2026Updated 2 months ago