abhayspawar / featexp
Feature exploration for supervised learning
☆763Updated 4 years ago
Alternatives and similar repositories for featexp:
Users that are interested in featexp are comparing it to the libraries listed below
- Automated vs Manual Feature Engineering Comparison. Implemented using Featuretools.☆327Updated 4 years ago
- ☆286Updated 2 years ago
- ML-Ensemble – high performance ensemble learning☆847Updated last year
- Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries☆704Updated 4 years ago
- XGBoost Feature Interactions Reshaped☆426Updated 7 years ago
- A set of useful tools for competitive data science.☆550Updated 2 years ago
- Automated feature engineering in Python with Featuretools☆516Updated 6 years ago
- Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one…☆380Updated 3 years ago
- StackNet is a computational, scalable and analytical Meta modelling framework☆1,319Updated 6 years ago
- ☆752Updated last year
- Distributed scikit-learn meta-estimators in PySpark☆285Updated 10 months ago
- Python package for stacking (machine learning technique)☆691Updated 6 months ago
- Code to compute permutation and drop-column importances in Python scikit-learn models☆607Updated 4 months ago
- ☆381Updated 7 years ago
- Personal data science and machine learning toolbox☆365Updated 5 years ago
- A library of sklearn compatible categorical variable encoders☆2,423Updated last month
- Leave One Feature Out Importance☆827Updated this week
- MLBox is a powerful Automated Machine Learning python library.☆1,508Updated last year
- python partial dependence plot toolbox☆850Updated 5 months ago
- Python implementations of the Boruta all-relevant feature selection method.☆1,550Updated 6 months ago
- ☆874Updated 5 years ago
- edaviz - Python library for Exploratory Data Analysis and Visualization in Jupyter Notebook or Jupyter Lab☆224Updated 5 years ago
- Implementation of Bayesian Hyperparameter Optimization of Machine Learning Algorithms☆625Updated last year
- XGBoost Feature Interactions & Importance☆498Updated 7 years ago
- 2nd Place Solution 💰🥈☆161Updated last year
- Hyper-parameter optimization for sklearn☆1,606Updated 8 months ago
- Features selector based on the self selected-algorithm, loss function and validation method☆675Updated 5 years ago
- Uplift modeling package.☆372Updated 2 years ago
- Code for Kaggle Data Science Competitions☆748Updated 9 months ago
- A Tiny, Pure Python implementation of Gradient Boosted Trees.☆253Updated 4 years ago