ivers 0.1.6

Python package to stratify split datasets based on endpoint distributions, also 2 different temporal splits. Chemprop compatible.

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}
}