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Multiple instance learning library for Python

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I am trying to dump a model and its metrics to the disk using pickle. You can see the [Metrics](https://github.com/rosasalberto/mil/blob/master/mil/metrics/custom.py#L7) class here. Is there any fix for this issue?

Resulted in large increase in performance. Also added distance metric configuration for application-specific performance options

used os.path.join to make referenced files work regardless of OS

I would like to install this package from source but there is no setup.py file. Is there a simple way to install this package from source for development?

``` (bags_train, y_train), (bags_test, y_test) = musk1.load() trainer = Trainer() metrics = [AUC, BinaryAccuracy] model = AttentionDeepPoolingMil(gated=False, threshold=0.4) pipeline = [('scale', StandarizerBagsList()), ('padding', Padding())] trainer.prepare(model, preprocess_pipeline=pipeline ,metrics=metrics) valid = KFold(n_splits=10,...

``` >>> from mil.data.datasets import musk1 >>> (bags_train, y_train), (bags_test, y_test) = musk1.load() Traceback (most recent call last): File "", line 1, in File "/usr/local/lib/python3.7/site-packages/mil/data/datasets/musk1.py", line 7, in load return...

Hi, Great Job! I am looking for multi-classification MIL. Could you please guide me how to use your package for my case? thanks!

Hey there, I'm having some trouble with the library and sorting out the dependencies. According to the docs, I need to install these: ``` pip install numpy pip install scikit-learn...

In other words, would pull requests get accepted or should the project get cloned in order to get updated instead?