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Added a summary of the most relevant features. The following are not included, as they seem too specific (not of use for readers I guess). Please let me know if you think otherwise.

Type Resolved Issues  
Enhancement #735 Use sklearn's ColumnTransformer for data preprocessing
Bug Fixing #769 Fixed error in calculation of meta features
Internal #793 Replace nosetests by pytest
Bug Fixing #799 Fix metalearning with same dataset name
Internal #784 Better budget handling
Internal #810 speed up minority coalescer
Enhancement #812 add new status type converged
Enhancement #823 #833 Update metadata 0.7.0

@mfeurer mfeurer merged commit 3ddb1e5 into automl:development May 7, 2020
charlesfu4 pushed a commit to charlesfu4/auto-sklearn that referenced this pull request Jun 17, 2020
* First version of 070 release notes

* Missed a bugfix

* Vim added unexpected space -- fix
mfeurer added a commit that referenced this pull request Jul 3, 2020
* PEP8 (#718)

* multioutput_regression

* multioutput_regression

* multioutput_regression

* multioutput regression

* multioutput regression

* multioutput regression

* multioutput regression

* multioutput regression

* #782 showcase pipeline components iteration

* Fixed flake-8 violations

* multi_output regression v1

* fix y_shape in multioutput regression

* fix xy_data_manager change due to merge

* automl.py missing import

* Release note 070 (#842)

* First version of 070 release notes

* Missed a bugfix

* Vim added unexpected space -- fix

* prepare new release (#846)

* Clip predict values to [0-1] in classification

* Fix for 3.5 python!

* Sensible default value of 'score_func' for SelectPercentileRegression (#843)

Currently default value of 'score_func' for SelectPercentileRegression
is "f_classif", which is an invalid value, and will surely be rejected and
will not work

* More robust tmp file naming (#854)

* More robust tmp file naming

* UUID approach

* 771 worst possible result (#845)

* Initial Commit

* Make worst result a function

* worst possible result in metric

* Fixing the name of the scorers

* Add exceptions to log file, not just stdout (#863)

* Add exceptions to log file, not just stdout

* Removing dummy pred as trys is not needed

* Add prediction with models trained with cross-validation (#864)

* add the possibility to predict with cross-validation

* fix unit tests

* test new feature, too

* 715 ml memory (#865)

* #715 Support for no ml memory limit

* API update

* Docs enhancement (#862)

* Improved docs

* Fixed example typos

* Beautify examples

* cleanup examples

* fixed rsa equal

* Move to minmax scaler (#866)

* Do not read predictions in memory, only after score (#870)

* Do not read predictions in memory, only after score

* Precission support for string/int

* Removal of competition manager (#869)

* Removal of competition manager

* Removed additional unused methods/files and moved metrics to estimator

* Fix meta data generation

* Make sure pytest is older newer than 4.6

* Unit tst fixing

* flake8 fixes in examples

* Fix metadata gen metrics

* Fix dataprocessing get params (#877)

* Fix dataprocessing get params

* Add clone-test to regression pipeline

* Allow 1-D threshold binary predictions (#879)

* fix single output regression not working

* regression need no _enusre_prediction_array_size_prediction_array_sizess

* #782 showcase pipeline components iteration

* Fixed flake-8 violations

* Release note 070 (#842)

* First version of 070 release notes

* Missed a bugfix

* Vim added unexpected space -- fix

* prepare new release (#846)

* Clip predict values to [0-1] in classification

* Fix for 3.5 python!

* Sensible default value of 'score_func' for SelectPercentileRegression (#843)

Currently default value of 'score_func' for SelectPercentileRegression
is "f_classif", which is an invalid value, and will surely be rejected and
will not work

* More robust tmp file naming (#854)

* More robust tmp file naming

* UUID approach

* 771 worst possible result (#845)

* Initial Commit

* Make worst result a function

* worst possible result in metric

* Fixing the name of the scorers

* Add exceptions to log file, not just stdout (#863)

* Add exceptions to log file, not just stdout

* Removing dummy pred as trys is not needed

* Add prediction with models trained with cross-validation (#864)

* add the possibility to predict with cross-validation

* fix unit tests

* test new feature, too

* 715 ml memory (#865)

* #715 Support for no ml memory limit

* API update

* Docs enhancement (#862)

* Improved docs

* Fixed example typos

* Beautify examples

* cleanup examples

* fixed rsa equal

* Move to minmax scaler (#866)

* Do not read predictions in memory, only after score (#870)

* Do not read predictions in memory, only after score

* Precission support for string/int

* Removal of competition manager (#869)

* Removal of competition manager

* Removed additional unused methods/files and moved metrics to estimator

* Fix meta data generation

* Make sure pytest is older newer than 4.6

* Unit tst fixing

* flake8 fixes in examples

* Fix metadata gen metrics

* Fix dataprocessing get params (#877)

* Fix dataprocessing get params

* Add clone-test to regression pipeline

* Allow 1-D threshold binary predictions (#879)

* multioutput_regression

* multioutput_regression

* multioutput_regression

* multioutput_regression

* multioutput_regression

* multioutput_regression

* multioutput regression

* multioutput regression

* multioutput regression

* multioutput regression

* multi_output regression v1

* fix y_shape in multioutput regression

* fix xy_data_manager change due to merge

* fix single output regression not working

* regression need no _enusre_prediction_array_size_prediction_array_sizess

* Add prediction with models trained with cross-validation (#864)

* add the possibility to predict with cross-validation

* fix unit tests

* test new feature, too

* multioutput_regression

* multioutput_regression

* multioutput_regression

* Removal of competition manager (#869)

* Removal of competition manager

* Removed additional unused methods/files and moved metrics to estimator

* Fix meta data generation

* Make sure pytest is older newer than 4.6

* Unit tst fixing

* flake8 fixes in examples

* Fix metadata gen metrics

* multioutput after rebased to 0.7.0

Problem:

Cause:

Solution:

* Regressor target y shape index out of range

* Revision for make tester

* Revision: Cancel Multiclass-MultiOuput

* Resolve automl.py metrics(__init__) reg_gb reg_svm

* Fix Flake8 errors

* Fix automl.py flake8

* Preprocess w/ mulitout reg,automl self._n_outputs

* test_estimator.py changed back

* cancel multioutput multiclass for multi reg

* Fix automl self._n_output update placement

* fix flake8

* Kernel pca cancelled mulitout reg

* Kernel PCA test skip python <3.8

* Add test unit for multioutput reg and fix.

* Fix flake8 error

* Kernel PCA multioutput regression

* default kernel to cosine, dodge sklearn=0.22 error

* Kernel PCA should be updated to 0.23

* Kernel PCA uses rbf kernel

* Kernel Pca

* Modify labels in reg, class, perpro in examples

* Kernel PCA

* Add missing supports to mincoal and truncateSVD

Co-authored-by: Matthias Feurer <[email protected]>
Co-authored-by: chico <[email protected]>
Co-authored-by: Francisco Rivera Valverde <[email protected]>
Co-authored-by: Xiaodong DENG <[email protected]>
franchuterivera added a commit to franchuterivera/auto-sklearn that referenced this pull request Aug 21, 2020
* First version of 070 release notes

* Missed a bugfix

* Vim added unexpected space -- fix
franchuterivera added a commit to franchuterivera/auto-sklearn that referenced this pull request Aug 21, 2020
* PEP8 (automl#718)

* multioutput_regression

* multioutput_regression

* multioutput_regression

* multioutput regression

* multioutput regression

* multioutput regression

* multioutput regression

* multioutput regression

* automl#782 showcase pipeline components iteration

* Fixed flake-8 violations

* multi_output regression v1

* fix y_shape in multioutput regression

* fix xy_data_manager change due to merge

* automl.py missing import

* Release note 070 (automl#842)

* First version of 070 release notes

* Missed a bugfix

* Vim added unexpected space -- fix

* prepare new release (automl#846)

* Clip predict values to [0-1] in classification

* Fix for 3.5 python!

* Sensible default value of 'score_func' for SelectPercentileRegression (automl#843)

Currently default value of 'score_func' for SelectPercentileRegression
is "f_classif", which is an invalid value, and will surely be rejected and
will not work

* More robust tmp file naming (automl#854)

* More robust tmp file naming

* UUID approach

* 771 worst possible result (automl#845)

* Initial Commit

* Make worst result a function

* worst possible result in metric

* Fixing the name of the scorers

* Add exceptions to log file, not just stdout (automl#863)

* Add exceptions to log file, not just stdout

* Removing dummy pred as trys is not needed

* Add prediction with models trained with cross-validation (automl#864)

* add the possibility to predict with cross-validation

* fix unit tests

* test new feature, too

* 715 ml memory (automl#865)

* automl#715 Support for no ml memory limit

* API update

* Docs enhancement (automl#862)

* Improved docs

* Fixed example typos

* Beautify examples

* cleanup examples

* fixed rsa equal

* Move to minmax scaler (automl#866)

* Do not read predictions in memory, only after score (automl#870)

* Do not read predictions in memory, only after score

* Precission support for string/int

* Removal of competition manager (automl#869)

* Removal of competition manager

* Removed additional unused methods/files and moved metrics to estimator

* Fix meta data generation

* Make sure pytest is older newer than 4.6

* Unit tst fixing

* flake8 fixes in examples

* Fix metadata gen metrics

* Fix dataprocessing get params (automl#877)

* Fix dataprocessing get params

* Add clone-test to regression pipeline

* Allow 1-D threshold binary predictions (automl#879)

* fix single output regression not working

* regression need no _enusre_prediction_array_size_prediction_array_sizess

* automl#782 showcase pipeline components iteration

* Fixed flake-8 violations

* Release note 070 (automl#842)

* First version of 070 release notes

* Missed a bugfix

* Vim added unexpected space -- fix

* prepare new release (automl#846)

* Clip predict values to [0-1] in classification

* Fix for 3.5 python!

* Sensible default value of 'score_func' for SelectPercentileRegression (automl#843)

Currently default value of 'score_func' for SelectPercentileRegression
is "f_classif", which is an invalid value, and will surely be rejected and
will not work

* More robust tmp file naming (automl#854)

* More robust tmp file naming

* UUID approach

* 771 worst possible result (automl#845)

* Initial Commit

* Make worst result a function

* worst possible result in metric

* Fixing the name of the scorers

* Add exceptions to log file, not just stdout (automl#863)

* Add exceptions to log file, not just stdout

* Removing dummy pred as trys is not needed

* Add prediction with models trained with cross-validation (automl#864)

* add the possibility to predict with cross-validation

* fix unit tests

* test new feature, too

* 715 ml memory (automl#865)

* automl#715 Support for no ml memory limit

* API update

* Docs enhancement (automl#862)

* Improved docs

* Fixed example typos

* Beautify examples

* cleanup examples

* fixed rsa equal

* Move to minmax scaler (automl#866)

* Do not read predictions in memory, only after score (automl#870)

* Do not read predictions in memory, only after score

* Precission support for string/int

* Removal of competition manager (automl#869)

* Removal of competition manager

* Removed additional unused methods/files and moved metrics to estimator

* Fix meta data generation

* Make sure pytest is older newer than 4.6

* Unit tst fixing

* flake8 fixes in examples

* Fix metadata gen metrics

* Fix dataprocessing get params (automl#877)

* Fix dataprocessing get params

* Add clone-test to regression pipeline

* Allow 1-D threshold binary predictions (automl#879)

* multioutput_regression

* multioutput_regression

* multioutput_regression

* multioutput_regression

* multioutput_regression

* multioutput_regression

* multioutput regression

* multioutput regression

* multioutput regression

* multioutput regression

* multi_output regression v1

* fix y_shape in multioutput regression

* fix xy_data_manager change due to merge

* fix single output regression not working

* regression need no _enusre_prediction_array_size_prediction_array_sizess

* Add prediction with models trained with cross-validation (automl#864)

* add the possibility to predict with cross-validation

* fix unit tests

* test new feature, too

* multioutput_regression

* multioutput_regression

* multioutput_regression

* Removal of competition manager (automl#869)

* Removal of competition manager

* Removed additional unused methods/files and moved metrics to estimator

* Fix meta data generation

* Make sure pytest is older newer than 4.6

* Unit tst fixing

* flake8 fixes in examples

* Fix metadata gen metrics

* multioutput after rebased to 0.7.0

Problem:

Cause:

Solution:

* Regressor target y shape index out of range

* Revision for make tester

* Revision: Cancel Multiclass-MultiOuput

* Resolve automl.py metrics(__init__) reg_gb reg_svm

* Fix Flake8 errors

* Fix automl.py flake8

* Preprocess w/ mulitout reg,automl self._n_outputs

* test_estimator.py changed back

* cancel multioutput multiclass for multi reg

* Fix automl self._n_output update placement

* fix flake8

* Kernel pca cancelled mulitout reg

* Kernel PCA test skip python <3.8

* Add test unit for multioutput reg and fix.

* Fix flake8 error

* Kernel PCA multioutput regression

* default kernel to cosine, dodge sklearn=0.22 error

* Kernel PCA should be updated to 0.23

* Kernel PCA uses rbf kernel

* Kernel Pca

* Modify labels in reg, class, perpro in examples

* Kernel PCA

* Add missing supports to mincoal and truncateSVD

Co-authored-by: Matthias Feurer <[email protected]>
Co-authored-by: chico <[email protected]>
Co-authored-by: Francisco Rivera Valverde <[email protected]>
Co-authored-by: Xiaodong DENG <[email protected]>
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2 participants