alteryx / Automated-Manual-Comparison
Automated vs Manual Feature Engineering Comparison. Implemented using Featuretools.
☆327Updated 4 years ago
Alternatives and similar repositories for Automated-Manual-Comparison:
Users that are interested in Automated-Manual-Comparison are comparing it to the libraries listed below
- Automated feature engineering in Python with Featuretools☆515Updated 6 years ago
- Feature exploration for supervised learning☆763Updated 4 years ago
- A collection of demos showcasing automated feature engineering and machine learning in diverse use cases☆500Updated last year
- Distributed scikit-learn meta-estimators in PySpark☆285Updated 10 months ago
- XGBoost Feature Interactions Reshaped☆427Updated 7 years ago
- Tools for WoE Transformation mostly used in ScoreCard Model for credit rating☆255Updated 5 years ago
- Deploy AutoML as a service using Flask☆226Updated 7 years ago
- My solution to Web Traffic Predictions competition on Kaggle.☆154Updated 6 years ago
- A general-purpose framework for solving problems with machine learning applied to predicting customer churn☆410Updated 8 months ago
- scikit-learn compatible projects☆410Updated 2 years ago
- edaviz - Python library for Exploratory Data Analysis and Visualization in Jupyter Notebook or Jupyter Lab☆224Updated 5 years ago
- Kaggle 8th place solution☆106Updated last year
- Python package that optimizes information value, weight-of-evidence monotonicity and representativeness of features for credit scorecard …☆117Updated 2 years ago
- 2nd Place Solution 💰🥈☆162Updated last year
- Features selector based on the self selected-algorithm, loss function and validation method☆675Updated 5 years ago
- Python implementation of the population stability index (PSI)☆138Updated last year
- Materials for an online-course - "Practical XGBoost in Python"☆218Updated 8 years ago
- Personal data science and machine learning toolbox☆365Updated 5 years ago
- Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries☆704Updated 4 years ago
- ☆136Updated 6 years ago
- ☆286Updated 2 years ago
- Predict whether a loan will be repaid using automated feature engineering.☆63Updated last year
- Feature Engineering Made Easy, published by Packt☆215Updated 2 years ago
- A set of useful tools for competitive data science.☆550Updated 2 years ago
- ☆101Updated 8 years ago
- 2nd Place Solution for Kaggle Porto Seguro's Safe Driver Prediction☆156Updated 5 years ago
- ☆34Updated 6 years ago
- Demand Forecasting Models for Kaggle competition☆81Updated 6 years ago
- Nyoka is a Python library that helps to export ML models into PMML (PMML 4.4.1 Standard).☆185Updated last year
- Address imbalance classes in machine learning projects.☆66Updated 6 years ago