Metadata-Version: 2.1
Name: grape-model
Version: 0.0.3
Summary: GRAPE makes it easy to fit a regression model with hyperparameter optimization.
Home-page: https://github.com/joshuacortez/grape
Author: Joshua Cortez
Author-email: joshua.m.cortez@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: scikit-learn
Requires-Dist: pandas
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: seaborn
Requires-Dist: xgboost
Requires-Dist: lightgbm
Requires-Dist: hyperopt


# GRAPE
GRAPE is a regression API in Python environment

# Description
GRAPE makes it easy to fit a regression model with hyperparameter optimization. It strings together the workflow of model fitting, hyperparameter tuning, and model diagnostics. (model interpretability coming soon!).
- Available Regression Methods
1. Elastic Net (from sklearn)
2. Random Forest (from sklearn)
3. xgboost
4. lightgbm
- Hyperparameter Optimization
    - Grape Uses Hyperopt's tree parzen estimator


