feature-engineering

https://github.com/microsoft/nni/blob/8d5f643c64580bb26a7b10a3c4c9accf617f65b1/nni/compression/pytorch/speedup/jit_translate.py#L382

While trying to speedup my single shot detector, the following error comes up. Any way to fix this,

/usr/local/lib/python3.8/dist-packages/nni/compression/pytorch/speedup/jit_translate.py in forward(self, *args)
    363 
    364         def forward(self, *

Once Woodwork implements this issue, we can clean up the Woodwork initialization in add_last_time_indexes to pass in the previous dataframe's table schema to keep that typing information but also perform inference on the new last time index column.

Is your feature request related to a problem? Please describe.
Currently in feature_store.yaml, we can only specify a region for DynamoDB provider. As a result, it requires an actual DynamoDB to be available when we want to do local development/testing or integration testing in a sandbox environment.

Describe the solution you'd like
A way to solve this is to let user pass an endpoint

Problem
Some of our transformers & estimators are not thoroughly tested or not tested at all.

Solution
Use OpTransformerSpec and OpEstimatorSpec base test specs to provide tests for all existing transformers & estimators.

When using r2 as eval metric for regression task (with 'Explain' mode) the metric values reported in Leaderboard (at README.md file) are multiplied by -1.
For instance, the metric value for some model shown in the Leaderboard is -0.41, while when clicking the model name leads to the detailed results page - and there the value of r2 is 0.41.
I've noticed that when one of R2 metric values in the L

The MultipleResultSetSQL class is derived from ::hybridse::sdk::ResultSet, and it's better to add override label to the overrode method.

The transformer should create computations over windows of past values of the features, and populate them at time t, t being the time of the forecast.

It uses pandas rolling, outputs several comptutations, mean, max, std, etc, and pandas shift to move the computations to the right row.

tmp = (data[variables]
       .rolling(window='3H').mean()  # Average the last 3 hr values.
       .

In #3324 , we had to mark some tests as expected to fail since XGBoost was throwing a FutureWarning. The warning has been addressed in XGBoost, so we're just waiting for the PR merged to be released. This issue is discussed in the #3275 issue.

evalml/tests/component_tests/test_xgboost_classifier.py needs to have the @pytest.mark.xfail removed f

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

We should implement useful implementations of:

class ResultMixin(object):
    """Base class housing the static function.

    Why a static function? That's because certain frameworks can only pickle a static function, not an entire
    object.
    """
    @staticmethod
    @abc.abstractmethod
    def build_