ethanglaser

Update job with infra branch: http://intel-ci.intel.com/ef02681e-c97c-f1ba-a9d0-a4bf010d0e2e

Latest CI with infra branch: http://intel-ci.intel.com/ef341186-2255-f106-a541-a4bf010d0e2e

There was mention of using https://github.com/intel/scikit-learn-intelex/blob/main/onedal/cluster/tests/test_dbscan.py#L52 logic for dbscan synthetic data generation, but on closer look its just a basic random data generation, not using epsilon or any dbscan params....

/intelci: run

Latest CI: http://intel-ci.intel.com/ef38b562-3e49-f1f9-894d-a4bf010d0e2e

> I suggest to use `get_dataframes_and_queues(dataframe_filter_="dpnp,dpctl", device_filter_="gpu",)`, `_as_numpy` and `_convert_to_dataframe` like in other algos modules testing. Thanks, addressed

Latest CI with infra branch: http://intel-ci.intel.com/ef3fe1d1-c22d-f1dc-b5ca-a4bf010d0e2e

> It looks like all tests are skipped in both public and private CI. is it expected? They will only run with GPU and dpctl (private CI GPU tests on...

Latest CI with infra branch: http://intel-ci.intel.com/ef4a161a-e33a-f1fc-b023-a4bf010d0e2e

> I see also that different dtypes are not tested here. Is this parametrizing skipped on purpose? Not on purpose - I will add it in. Good point.