baserush

PyPI

Stable base modeling made quick and easy!

baserush is an easy-to-use regression pipeline for preprocessing, optimizing, and summarizing machine learning models within the scikit-learn framework. This package is ideal for efficiently building and comparing stable models from different model types.

Supported Model Types

Linear Models

  • LinearRegression
  • Lasso
  • Ridge
  • SGDRegressor

Neighbors Models

  • KNeighborsRegressor
  • RadiusNeighborsRegressor

CaRT Models

  • DecisionTreeRegressor
  • ExtraTreeRegressor

Ensemble Models

  • RandomForestRegressor
  • GradientBoostingRegressor
  • ExtraTreesRegressor
  • RandomTreesEmbedding

Package Modules

  • preprocess: missing values, skewness, standardization, and categorical transformations
  • optimize: automatic feature selection; hyperparameter analysis
  • summary: training and validation R-Squared, stability tools; model-specific outputs

preprocessing Features

  • simputer makes it simple to flag and impute missing values.
  • Quickly alleviate skewness with transtorm.
  • Use simple_scaler to seamlessly standardize features.
  • Efficiently prepare categorical data for modeling with catcoder.

optimize-ation Features

  • Base modeling made easy with
    • quick_lm (with automated feature selection)
    • quick_tree, (includes very fast automated hyperparameter tuning)
    • quick_neighbors, (automatically tunes n neighbors)
  • Use tuning_results to analyze the top n-models after hyperparameter tuning with GridSeachCV | RandomizedSearchCV.

summary Features

lr_summary, tree_summary, and knn_summary

  • Automatically instantiate customizable training and validation sets.
  • Generate a dataset of model summaries for easy comparison, including:
    • Model Name
    • Model Class
    • Model Type
    • R-Squared (Training Set)
    • R-Squared (Validation Set)
    • Train-Test Gap
    • Model-Specific:
      • Model Coefficients
      • Feature Importance
      • Hyperparameter Values

Installation

Install using pip:

pip install baserush

Example Usage

print("Examples coming soon.")

License

MIT License. See LICENSE for details.