allenai/learning-curve

Library for computing classifier Learning Curves & iPython notebooks to improve your learning curve for using Learning Curves for ML research and practice!

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Experimental

This tool helps machine learning researchers and practitioners understand how their classifier's performance changes with varying amounts of training data. You provide error measurements from models trained on different subsets of your data, and it outputs a professional plot of the learning curve, including estimated error variance. This is ideal for those evaluating or comparing different machine learning models.

No commits in the last 6 months.

Use this if you need to visualize how your machine learning model's performance scales with more or less training data, or to compare the data efficiency of different models.

Not ideal if you're not working with machine learning classifiers or if you don't have the ability to train models on different subsets of your data.

machine-learning-research model-evaluation data-efficiency algorithm-comparison
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 8 / 25

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9

Forks

1

Language

Jupyter Notebook

License

Apache-2.0

Last pushed

May 28, 2021

Commits (30d)

0

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