Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Sparsity of data when values come from compute values #2322

Closed
nikicc opened this issue May 17, 2017 · 0 comments
Closed

Sparsity of data when values come from compute values #2322

nikicc opened this issue May 17, 2017 · 0 comments

Comments

@nikicc
Copy link
Contributor

nikicc commented May 17, 2017

Orange version

master

Expected behavior

When compute values produce sparse features (e.g. BoW), X array should become sparse not matter in which format (sparse/dense) it previously was and regardless of number of features (zero, non-zero) it previously had.

Actual behavior

Sparsity of X, Y and metas is determined from the sparsity of source data, regardless of the sparsity of data coming from compute values.

Steps to reproduce the behavior

Most easily on text. Learn a classifier on one BoW data and apply it on an other data that initially has some features.
screen shot 2017-05-17 at 18 58 03

Additional info (worksheets, data, screenshots, ...)
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant