modAL
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modAL-python
A modular active learning framework for Python
The learners should support `torch.Tensor` datatypes, see: #109
Per #80 made a DataManager class. Probably easiest to get a sense of it through the examples, but highlight is that users don't need to do bookeeping because they can...
In the documentation, only classifier is supported for Ranked batch-mode sampling. I am wondering whether regressor is supported? And if yes, how should we do it? Thanks in advance!
hello, I noticed there is a big focus on uncertainty based sampling and information density based sampling techniques which is very nice. but in batch mode active learning, when several...
Hi, I implemented the sample code here : https://modal-python.readthedocs.io/en/latest/content/apireference/models.html However, when i switched X(training data in the sample code) to X = np.linspace(0, 22, 1000).reshape(-1, 1) optimizer.score(X, y) gives me...
I wonder does modAL supports to pick data for neural net such as object detection model? Thanks a lot.
I am working with the ActiveLearner and I want to visualize the loss,accuracy after every query. I was wondering if teach is calling the fit method at every query because...
Hello.I found that Extending modAL can combine different methods of uncertainty.But I want to choose samples by both uncertainty and density.I use `linear_combination = make_linear_combination( classifier_uncertainty, information_density, weights=[1.0, 1.0] )`...
Hi, In the active learning for regression example, we have used gaussian processes. While the sklearn version seems to keep its length scale and noise parameters static ( maybe i...
It is common to build an sklearn pipeline, which includes the necessary data preprocessing (and feature encoding) steps and ends with an estimator (For example, see [Column Transformer with Mixed...
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A modular active learning framework for Python