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

[DOC] fix typo in classification notebook #5390

Merged
merged 1 commit into from Oct 9, 2023

Conversation

pirnerjonas
Copy link
Contributor

Reference Issues/PRs

What does this implement/fix? Explain your changes.

Fixing a typo in the classification notebook

Does your contribution introduce a new dependency? If yes, which one?

What should a reviewer concentrate their feedback on?

Did you add any tests for the change?

Any other comments?

PR checklist

For all contributions
  • I've added myself to the list of contributors with any new badges I've earned :-)
    How to: add yourself to the all-contributors file in the sktime root directory (not the CONTRIBUTORS.md). Common badges: code - fixing a bug, or adding code logic. doc - writing or improving documentation or docstrings. bug - reporting or diagnosing a bug (get this plus code if you also fixed the bug in the PR).maintenance - CI, test framework, release.
    See here for full badge reference
  • Optionally, I've added myself and possibly others to the CODEOWNERS file - do this if you want to become the owner or maintainer of an estimator you added.
    See here for further details on the algorithm maintainer role.
  • The PR title starts with either [ENH], [MNT], [DOC], or [BUG]. [BUG] - bugfix, [MNT] - CI, test framework, [ENH] - adding or improving code, [DOC] - writing or improving documentation or docstrings.
For new estimators
  • I've added the estimator to the API reference - in docs/source/api_reference/taskname.rst, follow the pattern.
  • I've added one or more illustrative usage examples to the docstring, in a pydocstyle compliant Examples section.
  • If the estimator relies on a soft dependency, I've set the python_dependencies tag and ensured
    dependency isolation, see the estimator dependencies guide.

@review-notebook-app
Copy link

Check out this pull request on  ReviewNB

See visual diffs & provide feedback on Jupyter Notebooks.


Powered by ReviewNB

Copy link
Collaborator

@fkiraly fkiraly left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Thanks. PR does what it claims, perfectly :-)

@fkiraly fkiraly changed the title doc: fix typo in classification notebook [DOC] fix typo in classification notebook Oct 9, 2023
@fkiraly fkiraly merged commit 4cbe9bd into sktime:main Oct 9, 2023
24 checks passed
@fkiraly fkiraly added documentation Documentation & tutorials module:classification classification module: time series classification labels Oct 9, 2023
yarnabrina added a commit to yarnabrina/sktime-fork that referenced this pull request Oct 10, 2023
* origin/main:
  [MNT] [Dependabot](deps-dev): Update arch requirement from <6.2.0,>=5.6.0 to >=5.6.0,<6.3.0 (sktime#5392)
  [BUG] `statsforecast 1.6.0` compatibility - fix argument differences between `sktime` and `statsforecast` (sktime#5393)
  [BUG] `statsforecast 1.6.0` compatibility - in `statsforecast` adapter, fixing `RuntimeError: dictionary changed size during iteration` (sktime#5317)
  [DOC] fix typo in classification notebook (sktime#5390)
  [DOC] fix broken docstring example of `AlignerDtwNumba` (sktime#5374)
  [ENH] incremental testing to also test if any parent class in sktime has changed (sktime#5379)
  [ENH] simplified delegator interface to `dtw-python` based dynamic time warping distances (sktime#5348)
  [ENH] `YfromX` - probabilistic forecasts (sktime#5271)
  [ENH] removed py37.dockerfile and update doc entry for CI (sktime#5356)
  [ENH] lucky dynamic time warping distance and aligner (sktime#5341)
  [ENH] sensible default `_get_distance_matrix` for time series aligners (sktime#5347)
  [ENH] delegator for pairwise time series distances and kernels (sktime#5340)
yarnabrina added a commit to yarnabrina/sktime-fork that referenced this pull request Oct 10, 2023
* origin/main:
  [MNT] [Dependabot](deps-dev): Update arch requirement from <6.2.0,>=5.6.0 to >=5.6.0,<6.3.0 (sktime#5392)
  [BUG] `statsforecast 1.6.0` compatibility - fix argument differences between `sktime` and `statsforecast` (sktime#5393)
  [BUG] `statsforecast 1.6.0` compatibility - in `statsforecast` adapter, fixing `RuntimeError: dictionary changed size during iteration` (sktime#5317)
  [DOC] fix typo in classification notebook (sktime#5390)
  [DOC] fix broken docstring example of `AlignerDtwNumba` (sktime#5374)
  [ENH] incremental testing to also test if any parent class in sktime has changed (sktime#5379)
  [ENH] simplified delegator interface to `dtw-python` based dynamic time warping distances (sktime#5348)
  [ENH] `YfromX` - probabilistic forecasts (sktime#5271)
  [ENH] removed py37.dockerfile and update doc entry for CI (sktime#5356)
  [ENH] lucky dynamic time warping distance and aligner (sktime#5341)
  [ENH] sensible default `_get_distance_matrix` for time series aligners (sktime#5347)
  [ENH] delegator for pairwise time series distances and kernels (sktime#5340)
yarnabrina added a commit to yarnabrina/sktime-fork that referenced this pull request Oct 10, 2023
* origin/split-ci:
  control pytest configuration
  [MNT] [Dependabot](deps-dev): Update arch requirement from <6.2.0,>=5.6.0 to >=5.6.0,<6.3.0 (sktime#5392)
  [BUG] `statsforecast 1.6.0` compatibility - fix argument differences between `sktime` and `statsforecast` (sktime#5393)
  [BUG] `statsforecast 1.6.0` compatibility - in `statsforecast` adapter, fixing `RuntimeError: dictionary changed size during iteration` (sktime#5317)
  [DOC] fix typo in classification notebook (sktime#5390)
  [DOC] fix broken docstring example of `AlignerDtwNumba` (sktime#5374)
  [ENH] incremental testing to also test if any parent class in sktime has changed (sktime#5379)
  [ENH] simplified delegator interface to `dtw-python` based dynamic time warping distances (sktime#5348)
  [ENH] `YfromX` - probabilistic forecasts (sktime#5271)
  [ENH] removed py37.dockerfile and update doc entry for CI (sktime#5356)
  [ENH] lucky dynamic time warping distance and aligner (sktime#5341)
  [ENH] sensible default `_get_distance_matrix` for time series aligners (sktime#5347)
  [ENH] delegator for pairwise time series distances and kernels (sktime#5340)
yarnabrina added a commit to yarnabrina/sktime-fork that referenced this pull request Oct 10, 2023
…recasting

* origin/split-ci:
  control pytest configuration
  [MNT] [Dependabot](deps-dev): Update arch requirement from <6.2.0,>=5.6.0 to >=5.6.0,<6.3.0 (sktime#5392)
  [BUG] `statsforecast 1.6.0` compatibility - fix argument differences between `sktime` and `statsforecast` (sktime#5393)
  [BUG] `statsforecast 1.6.0` compatibility - in `statsforecast` adapter, fixing `RuntimeError: dictionary changed size during iteration` (sktime#5317)
  [DOC] fix typo in classification notebook (sktime#5390)
  [DOC] fix broken docstring example of `AlignerDtwNumba` (sktime#5374)
  [ENH] incremental testing to also test if any parent class in sktime has changed (sktime#5379)
  [ENH] simplified delegator interface to `dtw-python` based dynamic time warping distances (sktime#5348)
  [ENH] `YfromX` - probabilistic forecasts (sktime#5271)
  [ENH] removed py37.dockerfile and update doc entry for CI (sktime#5356)
  [ENH] lucky dynamic time warping distance and aligner (sktime#5341)
  [ENH] sensible default `_get_distance_matrix` for time series aligners (sktime#5347)
  [ENH] delegator for pairwise time series distances and kernels (sktime#5340)
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
documentation Documentation & tutorials module:classification classification module: time series classification
Projects
None yet
Development

Successfully merging this pull request may close these issues.

None yet

2 participants