machine-learning-algorithms

Description of Change

Checklist

• Added description of change
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Description of Change

References

Checklist

Discussed in microsoft/nni#4070

[2021-08-14 10:13:41] INFO (NNIDataStore) Datastore initialization done
[2021-08-14 10:13:41] INFO (RestServer) RestServer start
[2021-08-14 10:13:41] INFO (RestServer) RestServer base port is 8080
[2021-08-14 10:13:41] I

Is your feature request related to a problem? Please describe.

The row_equality_comparator constructor currently accepts a bool to indicate if nulls are considered equal or not. In libcudf, we prefer to use scoped enums instead of bools and we already have a [`

Description

We want to add support for auto ML. My suggestion is to use autokeras. I'm letting this open for newcomers who want to contribute to this project.

The parameters of the model need to be read from a yaml file (check utils.py in igel, there is a helper function to read a yaml or json file). These parameters will be used to construct and train a model. The results should be th

Report needed documentation

Report needed documentation
While the estimator guide offers a great breakdown of how to use many of the tools in api_context_managers.py, it would be helpful to have information right in the docstring during development to more easily understand what is actually going on in each of the provided functions/classes/methods. This is particularly important for

Description

Currently our unit tests are disorganized and each test creates example StellarGraph graphs in different or similar ways with no sharing of this code.

This issue is to improve the unit tests by making functions to create example graphs available to all unit tests by, for example, making them pytest fixtures at the top level of the tests (see https://docs.pytest.org/en/latest/

Hi, Thanks for the awesome library!

So I am running a Kmeans on lots of different datasets, which all have roughly four shapes, so I initialize with those shapes and it works well, except for just a few times. There are a few datasets that look different enough that I end up with empty clusters and the algorithm just hangs ("Resumed because of empty cluster" again and again).

I conceptually