Add better print behavior for low_order_moments() about scikit-learn-intelex HOT 5 CLOSED

It's a matter of implementing __str__ method for the result.

The result may contain the following fields: minimum, maximum, mean, standardDeviation, variance, variation, sum, sumSquared, sumSquaresCentered, secondOrderRawMoment.

I suppose the default 'smart' printing would display min, max, mean and std if available, kind of like summary function does in R.

It makes sense to arrange the data into a table. Perhaps reuse pandas for printing?

How about a code that maps low_order_result to a pandas's dataframe?

from scikit-learn-intelex.

I would like to think about the broader picture. The same 'issue' exists for all results/models.

I suggest adding a __str__ method to all results and models

• printing attribute names and value for standard/trivial types (integer, str, float etc)
• printing attribute name and a summary for non-trivial, non-daal types
  • 'array' (or similar), dtype and shape for numpy arrays
  • 'dict' (or alike) and size
  • as far as I can tell there are no other non-trivial, non-daal types used
• printing attribute name and daal type for daal types (like models)

Attributes which are not expanded (complex and daal types) can be expanded by explicitly printing them.

A conversion to a pandas data-frame seems applicable only in very special cases, like low order moments. A conversion to a dict looks more generic. pandas allows creating DFs from dicts.

@Alexander-Makaryev

from scikit-learn-intelex.

For algorithms we could print the parameters. This is more involved and probably less important.

from scikit-learn-intelex.

Yes, I'll second @fschlimb 's findings. It is mostly about having str methods when looking at a summary, and accessors to the values in the right type when needing a specific one (mean, variance as examples).

from scikit-learn-intelex.

done: generic print capability added for results and model through #48

from scikit-learn-intelex.