Tamar Grey
Tamar Grey
- As a user, I wish I could use the Ordinal Encoder to encode Ordinal columns whose categories' orders are not in strictly increasing numeric order. The following code raises...
After fast mode is added, we should add it to EvalML docs so we can tell users about fast mode, its benefits, and its limitations.
Partial dependence fast mode was initially added with some limitations, namely that it will not produce correct results if any of the components in the pipeline relies on multiple columns...
In partial dependence fast mode, we precompute `pipeline.transform_all_but_final(X_eval)`, which allows us to determine if a feature will have an impact on model results and, if it won't, use averaged predictions...
In the initial implementation of partial dependence fast mode in #3753, the Oversampler was causing a few pipelines to produce different partial dependence results in fast mode. After understanding why...
- As a user, I wish I had an easy way to tell the difference between two Woodwork TableSchemas. When passing around Woodwork dataframes, it is easy to lose track...
`WoodworkTableAccessor._filter_cols` is used by `select` and `describe`, and it takes in a single `include` parameter that tries to determine what is a semantic tag vs logical type vs column name....
There are situations where we may instantiate an Ordinal logical type for a column based on training data, and then when we see the holdout data, there may be new...
- As a user, I wish I could use `ww.init_series` to initialize a series with an existing woodwork column schema. It's possible to do with with `series.ww.init`, and it'd be...
Koalas DataFrames cannot be deepcopied, so currently `EntitySet.__deepcopy__` will not work for EntitySets with koalas dataframes. The tests for EntitySet.concat xfail for koalas because "Koalas deepcopy fails", so this is...