Explore how datasets shape classifier biases
Visualize dataset distributions with facets
Create detailed data reports
Display color charts and diagrams
Uncensored General Intelligence Leaderboard
Try the Hugging Face API through the playground
Migrate datasets from GitHub or Kaggle to Hugging Face Hub
Analyze and visualize your dataset using AI
Analyze your dataset with guided tools
Generate a data report using the pandas-profiling tool
Submit evaluations for speaker tagging and view leaderboard
Make RAG evaluation dataset. 100% compatible to AutoRAG
Compare classifier performance on datasets
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.