Bug Report

These tests were run on s390x. s390x is big-endian architecture.

Failure log for helper_test.py

________________________________________________ TestHelperTensorFunctions.test_make_tensor ________________________________________________

self = <helper_test.TestHelperTensorFunctions testMethod=test_make_tensor>

    def test_make_tensor(self):  # type: () -> None
    

Like xarray, pandas supports attaching arbitrary metadata to DataFrames and persisting it across operations. https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.attrs.html

Dask could pretty easily implement this as well. We'd have a

• _Frame.attrs property. This would likely return self._meta.attrs.
• We'd verify that dd.from_pandas(data) correctly extracts attrs from `da

For example, if there is a relationship transaction.session_id -> sessions.id and we are calculating a feature transactions: sessions.SUM(transactions.value) any rows for which there is no corresponding session should be given the default value of 0 instead of NaN.

Of course this should not normally occur, but when it does it seems more reasonable to use the default_value.

`DirectF

with the Power Transformer.

I see the code

device = ‘cuda’ if torch.cuda.is_available() else ‘cpu’

repeated often in user code. Maybe we should introduce device='auto' exactly for this case?

Yes

How do i resume training for text classification?

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

it would be useful for users to be able to download the classification/regression problems directly from timeseriesclassification.com in code. Apparently tslearn does this, and it seems like a good idea

Describe the solution you'd like
I'm not sure where it should be located, perhaps with the load data tools

**Describ

Description

In the future, igel should support multiple dataset format other than csv. Maybe add support for excel, json and sql tables.

It would be great if users have the flexibility of providing their datasets in other formats and not only csv.

I think it could be useful, when one wants to plot only e.g. class 1, to have an option to produce consistent plots for both plot_cumulative_gain and plot_roc

At the moment, instead, only plot_roc supports such option.

Thanks a lot