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Data-leak is a Visual QA tool designed to help users explore and address data leakage in machine learning models. It provides insights into potential issues where infor/leak from training data may influence model performance, ensuring more robust and fair results.
What is data leakage in machine learning?
Data leakage occurs when information from the training data unintentionally influences the model’s predictions, often leading to overfitting and poor generalization.
Can data-leak work with any machine learning model?
Yes, data-leak is designed to be compatible with most machine learning models, providing universal insights into data quality and potential leakage.
How does data-leak visualize the results?
Data-leak uses interactive and static visualizations, such as heatmaps, scatterplots, and correlation matrices, to present findings in an actionable manner.