AMFRegressor #1166
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AMFRegressor #1166
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- Adding a "mondrian" folder in the "tree" folder for better file structure - Using "random.choices" instead of the "sample_discrete" functions in "utils.py", and removing "sample_discrete" from the "utils.py"
- Making `learn_one` and `predict_proba_one` accepting all kinds of supported labels for `y` as input - `predict_proba_one` outputs a dictionary of scores with matching labels
Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br>
Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br>
Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br>
Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br>
- Leaving `__all__` in alphabetical order for the classifiers - Removing type parameters in the description of `log_2_sum` of math utils - Replacing java-like getters and setters by python-like properties and setter
- Replacing Overflow from infinity to maximum possible float (so it makes computations still possible)
Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br>
- Fixing import order in __init__ file of ensemble - Using LaTeX formulation in AMFClassifier description - Making all nodes related methods private (it shouldn't be used outside) - Docstring syntax update and fixes - Importing river.base instead of typing module for better readability - Adding a short description to the MondrianTreeClassifier - Renaming MondrianTreeLeaf into MondrianLeaf - Reordering functions in MondrianTreeClassifier for better readability
- Trying to fix the left-right issue uppercast (that shouldn't be a problem normally, but mypy keeps being unhappy) - Fixing assignment issue to the parent during upward procedure - Fixing type assignment to the root branch of the tree - Fixing arg-type for list of intensities - Fixing arg-type issue with current samples proceeding - Fixing dirichlet arg-type issue - Fixing some typing issues - Removing call-overload as int in the memories features range list - Correcting output of predict function
suggestions and style issues fix
…instead of raising an exception
fix remaining tests and remove duplicated method call
- Adding examples for AMF & Mondrian Tree Classifiers - Reordering __init__ in alphabetical order - Cleaning the comments - Adding string representation for nodes
Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br>
kenzabenjelloun
requested review from
MaxHalford and
smastelini
as code owners
|
Hey there, great work! I hope you still managed to find time to enjoy your weekend :) I'm guessing Saulo will be ok reviewing this PR, although I know he's a bit busy at the moment. One first comment: since we merged Alexandre's PR, we reorganized stuff and create a new |
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Hi @kenzabenjelloun, thanks for the PR! As @MaxHalford mentioned, there are some conflicts to solve. Once everything is in place, I will start reviewing the code :D |
MaxHalford
reviewed
Jan 24, 2023
added 2 commits
January 24, 2023 18:13
smastelini
requested changes
Jan 26, 2023
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Hi @kenzabenjelloun, thanks for bringing the AMF Regressor! I can't wait to put this model to the test :)
I have left some comments in your code, as well as some questions for further clarification.
Some time ago, you mentioned there was a bug that affected performance. Were you able to track this down?
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| split_pure | ||
| Controls if nodes that contains only sample of the same class should be | ||
| split ("pure" nodes). Default is `False`, namely pure nodes are not split, | ||
| but `True` can be sometimes better. |
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I am not sure this applies to regression, since there are no classes.
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| Note | ||
| ---- | ||
| All the parameters of ``AMFRegressor`` become **read-only** after the first call | ||
| to ``partial_fit``. |
There was a problem hiding this comment.
I'm also not sure this applies in this case.
| super().__init__(*args, **kwargs) | ||
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| self.n_samples = 0 | ||
| self.mean = 0.0 |
There was a problem hiding this comment.
You can use an instance of stats.Mean() instead, to avoid hardcoding the mean update.
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Hi @kenzabenjelloun, was there any progress in finding the performance bug? I just fixed a conflict with the main branch and resolved some comments you already addressed. |
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Hi @kenzabenjelloun and @MaxHalford. I've changed the target branch of this PR to a new branch. If you agree, I will merge the PR and take on the remaining work. |
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hi @smastelini ! yes, perfect thank you |
smastelini
added a commit
that referenced
this pull request
Jul 6, 2023
* AMF Classifier & Mondrian Tree Classifier implementation * [Pull request Update] - Adding a "mondrian" folder in the "tree" folder for better file structure - Using "random.choices" instead of the "sample_discrete" functions in "utils.py", and removing "sample_discrete" from the "utils.py" * [Pull Request] - Removing the "__repr__" method of AMF - Removing the @Setter and @getter - Removing the "loss" parameter of the classifiers since only the "log-loss" is being used in the end * Updating docstring * [Pull request] - Making `learn_one` and `predict_proba_one` accepting all kinds of supported labels for `y` as input - `predict_proba_one` outputs a dictionary of scores with matching labels * [Fix] Reability Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br> * [Fix] Language Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br> * [Fix] Language Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br> * [Fix] math package implementation usage Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br> * [Pull request] - Leaving `__all__` in alphabetical order for the classifiers - Removing type parameters in the description of `log_2_sum` of math utils - Replacing java-like getters and setters by python-like properties and setter * - Adding support for random state (seed) - Replacing Overflow from infinity to maximum possible float (so it makes computations still possible) * [Ignoring testing environment] * Fixing style & typos Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br> * [Pull request] - Fixing import order in __init__ file of ensemble - Using LaTeX formulation in AMFClassifier description - Making all nodes related methods private (it shouldn't be used outside) - Docstring syntax update and fixes - Importing river.base instead of typing module for better readability - Adding a short description to the MondrianTreeClassifier - Renaming MondrianTreeLeaf into MondrianLeaf - Reordering functions in MondrianTreeClassifier for better readability * Pre-commit clean up * Pre-commit clean up * [MyPy issue] - Trying to fix the left-right issue uppercast (that shouldn't be a problem normally, but mypy keeps being unhappy) - Fixing assignment issue to the parent during upward procedure - Fixing type assignment to the root branch of the tree - Fixing arg-type for list of intensities - Fixing arg-type issue with current samples proceeding - Fixing dirichlet arg-type issue - Fixing some typing issues - Removing call-overload as int in the memories features range list - Correcting output of predict function * Fixing MyPy issues (detyping) * suggestions and style issues fix * addingnecessary files, classes and methods for regressor * minor import modifications * minor list to typing.List and dict to typing.Dict modifs * minor modifs to pass tests * minor changes * changing names * Fixing predict function to support the "model not trained" situation instead of raising an exception * more style suggestions * testing * regressor fix * fixing docstring * [Pull request Update] - Fixing some TODOs from Mastelini suggestions - Factorizing a bit of code from nodes that should be shared with regressor - Removing branch structure as of now for future changes * Removing all "array-like" structure for full dict support * Pre-commit hookups fixes * regressor fix * Delete tests.py * [Pull request] - Adding suggestions from Mastelini on keys usage - Removing useless initialization of scores in the MondrianTreeClassifier * bug fix * fix conflicts * refactored, but has bugs * remove mypy skip * tests * tests * cleanup * better, but not fixed * minor fix * [Fixes] - Fixing scoring bug (no propagation of counts) - Removing unused parameters in docs - Replacing type union of Python 3.10 in 3.9 annotations - Adding little description for MondrianBranch * Pre-commit hookups fixes * fix some tests * Reworking intensities * fix remaining tests and remove duplicated method call * [Pull request] - Adding examples for AMF & Mondrian Tree Classifiers - Reordering __init__ in alphabetical order - Cleaning the comments - Adding string representation for nodes * Hiding MondrianTree from users visibility * Fixing import on Mondrian Tree example Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br> * tests * merge fix * merge fix * docstring fixes --------- Co-authored-by: AlexandreChaussard <alexandre.chaussard@telecom-sudparis.eu> Co-authored-by: Alexandre Chaussard <78101027+AlexandreChaussard@users.noreply.github.com> Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br> Co-authored-by: Kenza Ben jelloun <kenza.ben_jelloun@telecom-sudparis.eu> Co-authored-by: Saulo Martiello Mastelini <saulomastelini@gmail.com>
smastelini
added a commit
that referenced
this pull request
Jul 11, 2023
* AMFRegressor (#1166) * AMF Classifier & Mondrian Tree Classifier implementation * [Pull request Update] - Adding a "mondrian" folder in the "tree" folder for better file structure - Using "random.choices" instead of the "sample_discrete" functions in "utils.py", and removing "sample_discrete" from the "utils.py" * [Pull Request] - Removing the "__repr__" method of AMF - Removing the @Setter and @getter - Removing the "loss" parameter of the classifiers since only the "log-loss" is being used in the end * Updating docstring * [Pull request] - Making `learn_one` and `predict_proba_one` accepting all kinds of supported labels for `y` as input - `predict_proba_one` outputs a dictionary of scores with matching labels * [Fix] Reability Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br> * [Fix] Language Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br> * [Fix] Language Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br> * [Fix] math package implementation usage Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br> * [Pull request] - Leaving `__all__` in alphabetical order for the classifiers - Removing type parameters in the description of `log_2_sum` of math utils - Replacing java-like getters and setters by python-like properties and setter * - Adding support for random state (seed) - Replacing Overflow from infinity to maximum possible float (so it makes computations still possible) * [Ignoring testing environment] * Fixing style & typos Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br> * [Pull request] - Fixing import order in __init__ file of ensemble - Using LaTeX formulation in AMFClassifier description - Making all nodes related methods private (it shouldn't be used outside) - Docstring syntax update and fixes - Importing river.base instead of typing module for better readability - Adding a short description to the MondrianTreeClassifier - Renaming MondrianTreeLeaf into MondrianLeaf - Reordering functions in MondrianTreeClassifier for better readability * Pre-commit clean up * Pre-commit clean up * [MyPy issue] - Trying to fix the left-right issue uppercast (that shouldn't be a problem normally, but mypy keeps being unhappy) - Fixing assignment issue to the parent during upward procedure - Fixing type assignment to the root branch of the tree - Fixing arg-type for list of intensities - Fixing arg-type issue with current samples proceeding - Fixing dirichlet arg-type issue - Fixing some typing issues - Removing call-overload as int in the memories features range list - Correcting output of predict function * Fixing MyPy issues (detyping) * suggestions and style issues fix * addingnecessary files, classes and methods for regressor * minor import modifications * minor list to typing.List and dict to typing.Dict modifs * minor modifs to pass tests * minor changes * changing names * Fixing predict function to support the "model not trained" situation instead of raising an exception * more style suggestions * testing * regressor fix * fixing docstring * [Pull request Update] - Fixing some TODOs from Mastelini suggestions - Factorizing a bit of code from nodes that should be shared with regressor - Removing branch structure as of now for future changes * Removing all "array-like" structure for full dict support * Pre-commit hookups fixes * regressor fix * Delete tests.py * [Pull request] - Adding suggestions from Mastelini on keys usage - Removing useless initialization of scores in the MondrianTreeClassifier * bug fix * fix conflicts * refactored, but has bugs * remove mypy skip * tests * tests * cleanup * better, but not fixed * minor fix * [Fixes] - Fixing scoring bug (no propagation of counts) - Removing unused parameters in docs - Replacing type union of Python 3.10 in 3.9 annotations - Adding little description for MondrianBranch * Pre-commit hookups fixes * fix some tests * Reworking intensities * fix remaining tests and remove duplicated method call * [Pull request] - Adding examples for AMF & Mondrian Tree Classifiers - Reordering __init__ in alphabetical order - Cleaning the comments - Adding string representation for nodes * Hiding MondrianTree from users visibility * Fixing import on Mondrian Tree example Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br> * tests * merge fix * merge fix * docstring fixes --------- Co-authored-by: AlexandreChaussard <alexandre.chaussard@telecom-sudparis.eu> Co-authored-by: Alexandre Chaussard <78101027+AlexandreChaussard@users.noreply.github.com> Co-authored-by: Saulo Martiello Mastelini <mastelini@usp.br> Co-authored-by: Kenza Ben jelloun <kenza.ben_jelloun@telecom-sudparis.eu> Co-authored-by: Saulo Martiello Mastelini <saulomastelini@gmail.com> * fix exponential sampling * lint * mypy * AMF Reg * documentation * expose exponential sampling * fix mypy * release notes * Update docs/releases/unreleased.md Co-authored-by: Max Halford <maxhalford25@gmail.com> * Update river/forest/aggregated_mondrian_forest.py Co-authored-by: Max Halford <maxhalford25@gmail.com> * Update river/utils/random.py Co-authored-by: Max Halford <maxhalford25@gmail.com> * fix docstrings * add missing import --------- Co-authored-by: kenzabenjelloun <74252706+kenzabenjelloun@users.noreply.github.com> Co-authored-by: AlexandreChaussard <alexandre.chaussard@telecom-sudparis.eu> Co-authored-by: Alexandre Chaussard <78101027+AlexandreChaussard@users.noreply.github.com> Co-authored-by: Kenza Ben jelloun <kenza.ben_jelloun@telecom-sudparis.eu> Co-authored-by: Max Halford <maxhalford25@gmail.com>
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Hi ! I am working on the AMF Regressor. This is what has been done so far, I tried to keep the same structure as the classifier. There is still a bug somewhere that I can't seem to find.. Thank you for your help !