AutoViML / featurewiz
Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.
☆637Updated last month
Alternatives and similar repositories for featurewiz:
Users that are interested in featurewiz are comparing it to the libraries listed below
- A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.☆613Updated last year
- A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.☆577Updated 10 months ago
- Linear Prediction Model with Automated Feature Engineering and Selection Capabilities☆513Updated 3 weeks ago
- EvalML is an AutoML library written in python.☆805Updated this week
- Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ra…☆752Updated 7 months ago
- A power-full Shapley feature selection method.☆204Updated 11 months ago
- Feature engineering package with sklearn like functionality☆2,028Updated 3 weeks ago
- A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.☆1,365Updated this week
- Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upo…☆535Updated 2 months ago
- Scalable machine 🤖 learning for time series forecasting.☆1,008Updated 2 weeks ago
- Fast SHAP value computation for interpreting tree-based models☆537Updated last year
- An extension of LightGBM to probabilistic modelling☆302Updated 10 months ago
- Flexible time series feature extraction & processing☆415Updated 7 months ago
- Calculates various features from time series data. Python implementation of the R package tsfeatures.☆402Updated 11 months ago
- Optimal binning: monotonic binning with constraints. Support batch & stream optimal binning. Scorecard modelling and counterfactual expl…☆468Updated last month
- All Relevant Feature Selection☆131Updated last week
- A library for debugging/inspecting machine learning classifiers and explaining their predictions☆287Updated this week
- XGBoost + Optuna☆697Updated 7 months ago
- Multiple Imputation with LightGBM in Python☆375Updated 8 months ago
- mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.☆581Updated 4 months ago
- Leave One Feature Out Importance☆832Updated 2 months ago
- The practitioner's forecasting library☆334Updated 2 weeks ago
- Machine learning for dataframes☆1,352Updated this week
- SHAP-based validation for linear and tree-based models. Applied to binary, multiclass and regression problems.☆137Updated this week
- A machine learning tool for automated prediction engineering. It allows you to easily structure prediction problems and generate labels f…☆505Updated 2 weeks ago
- A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.☆468Updated last year
- A python package for time series forecasting with scikit-learn estimators.☆161Updated last year
- An extension of XGBoost to probabilistic modelling☆593Updated 9 months ago
- Forecasting with Gradient Boosted Time Series Decomposition☆195Updated last year
- Extra blocks for scikit-learn pipelines.☆1,315Updated 3 weeks ago