ivers 0.1.20

Python package to stratify split datasets based on endpoint distributions

Ivers

This project offers tools for managing data splits, ensuring endpoint distributions are maintained, and presents two novel temporal split techniques: 'leaky' and 'all for free' splits. See the explanation below.

Note: This library was used in this paper PlaceHolder to generate the data splits.

Features

• Temporal Leaky: Allows for forward-leakage in your data to simulate real-world scenarios where future data might influence the model subtly.
• Temporal AllForFree: Provides a stricter temporal separation, ensuring that the training data is entirely independent of the test set, suitable for rigorous testing of model predictions over time.
• Temporal Fold Split: Implements a novel approach to increasing the training set size successively across multiple folds based on the temporal time sequence
• Stratified Endpoint Split: Our library introduces a stratified endpoint split, crucial for maintaining a consistent distribution of data across different categories or endpoints in your datasets. Especially useful in scenarios where endpoint distributions are critical, such as in cheminformatics and bioinformatics.
• Cross-Validation Support: Integrates capabilities to ensure that each cross-validation split maintains endpoint distribution, ideal for developing models that are generalizable across varied data conditions.

Integration with Chemprop

• By setting the chemprop variable to true, the library will generate splits compatible with the Chemprop library. This ensures that the features and train-test splits are generated in a way that can easily be used with Chemprop.

Getting Started or Contributing

To get started with this library, clone the repository and install the required dependencies:

git clone https://github.com/IversOhlsson/ivers.git
cd ivers
pip install -r requirements.txt

Installation via pip

You can also install the package via pip:

pip install ivers

We welcome contributions! Feel free to open issues or pull requests on our GitHub repository.

Guide

Reference

when using this library, please cite the following paper:

@article{Ivers_1,
  title={PlaceHolder},
  author={PlaceHolder},
  journal={PlaceHolder},
  volume={PlaceHolder},
  number={PlaceHolder},
  pages={PlaceHolder},
  year={PlaceHolder},
  publisher={PlaceHolder}
}