miriamspsantos/open-source-imbalance-overlap

A collection of Open Source Contributions in Learning from Imbalanced and Overlapped Data

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This project helps data scientists and machine learning practitioners build more accurate predictive models, especially when dealing with tricky datasets. It provides a curated list of open-source tools and code for handling data where one outcome is much rarer than others (class imbalance) or where different groups of data points are difficult to tell apart (class overlap). You'll find resources to preprocess your data, generate synthetic examples, and apply specialized algorithms to improve model performance.

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Use this if you are a data scientist or machine learning practitioner struggling with poor model performance due to imbalanced or overlapping data in classification tasks.

Not ideal if you are looking for a single, ready-to-use software application rather than a collection of code and research resources.

predictive-modeling data-preprocessing machine-learning-optimization classification-tasks
No License Stale 6m No Package No Dependents
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Adoption 6 / 25
Maturity 8 / 25
Community 12 / 25

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Last pushed

Dec 30, 2021

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