modAL
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modAL-python
A modular active learning framework for Python
This pull request introduces an embedding-based sampling method in an active learning pipeline for CIFAR-10. The key update is the way we select informative samples from the pool dataset after...
Hello! I would love to contribute to modAL, I feel like there are not many examples of regression problems in the documentation. I can try to add my touch to...
I am writing my master thesis on imbalanced dataset impact on active learning methods. I have stumbled upon a problem in bootstrapping. When there is few minority class samples, sometimes...
Adding stratified bootstrap. It can be useful for imbalanced datasets and avoiding: `ValueError: The number of classes has to be greater than one; got 1 class` error, by ensuring minority...
import modAL is not working. Most of the modules that is found in the official documentation is not working
Hello, Does the QBC approach support multi-class classification? Thanks for the clarification.
Hi! I am wondering, which of the implemented sampling strategies handles unbalanced data best? I believe if I get the top 10000 uncertain data instances, but 99 % are in...
Hi there, I have already trained some good working estimators (xgboost, catboost & lightgbm). I would like to add an active learner, because we need to decide which data to...
Corrected several style issues. Some are aesthetic, others risk introducing bugs.
Includes #172 It is poor practice to use unrestricted except clauses. This has resulted in multiple errors going unnoticed. I have removed these clauses and replaced with more specific (and...
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A modular active learning framework for Python