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dataset-worldviews is a powerful tool designed to explore and analyze how different datasets influence the biases of classifiers. It provides insights into how various data compositions can shape the behavior and decision-making of machine learning models. By examining these relationships, users can better understand and address potential biases in their datasets.
What types of biases can dataset-worldviews detect?
dataset-worldviews can identify various types of biases, including selection bias, confirmation bias, and imbalanced class distributions.
How do I handle imbalanced data using dataset-worldviews?
The tool offers several strategies, including resampling techniques, cost-sensitive learning, and data augmentation.
What file formats does dataset-worldviews support?
dataset-worldviews supports common formats such as CSV, Excel, and Pandas DataFrames.