modAL
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A modular active learning framework for Python
Not sure if there is any desire for this feature, but in this PR I have sketched out a way to use virtually any estimator type with the `ActiveLearner` and...
trying to run this notebook https://www.kaggle.com/code/kmader/active-learning-optimization-improvement/notebook getting an error in `learner.teach` step (and also in `pd.concat(seq_iter.compute())` step): ``` # initializing the learner from modAL.models import ActiveLearner initial_df = all_papaya_samples_df.sample(20, random_state=2018)...
I am trying to apply the package for sklearn RandomForestClassifier like this: ``` learner= ActiveLearner( estimator=RandomForestClassifier(), query_strategy=modAL.uncertainty.uncertainty_sampling, X_training=X_train0, y_training=y_train ) learner ``` Then the following error appears: ``` --------------------------------------------------------------------------- AttributeError...
Several non-probabilistic estimators, such as SVMs in particular, can be used with uncertainty sampling. Scikit-Learn estimators that support the decision_function method can be used with the closest-to-hyperplane selection algorithm [[Bloodgood]](https://arxiv.org/pdf/1801.07875.pdf)....
Implement the hierarchical sampling algorithm from [Dasgupta and Hsu paper](https://dl.acm.org/citation.cfm?id=1390183).
url typo
I am using the Keras script at https://modal-python.readthedocs.io/en/latest/content/examples/Keras_integration.html for my classification task. After completing the active learning loop, how do we extract the image names and labels in the training...
Hi, Thanks for this nice tool. I am quite a beginner in the optimization field and I am wondering if ModAL supports also multi-objective optimization? As if I would include...
Can a multivariate Active regression be performed with this package? If so, could anyone provide an example?
Hi there, I would like to apply active learning to a keras model trained with another script. The model, with architecture, is stored in a .h5 file. I followed the...