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  1. 14 Jul, 2020 1 commit
  2. 07 Jul, 2020 1 commit
  3. 28 Jun, 2020 1 commit
    • Ilya Matiach's avatar
      adding sparse support to TreeSHAP in lightgbm (#3000) · 9f367d11
      Ilya Matiach authored
      * adding sparse support to TreeSHAP in lightgbm
      
      * updating based on comments
      
      * updated based on comments, used fromiter instead of frombuffer
      
      * updated based on comments
      
      * fixed limits import order
      
      * fix sparse feature contribs to work with more than int32 max rows
      
      * really fixed int64 max error and build warnings
      
      * added sparse test with >int32 max rows
      
      * fixed python side reshape check on sparse data
      
      * updated based on latest comments
      
      * fixed comments
      
      * added CSC INT32_MAX validation to test, fixed comments
      9f367d11
  4. 27 Jun, 2020 1 commit
    • Alex's avatar
      [python][scikit-learn] new stacking tests and make number of features a property (#3173) · 72849466
      Alex authored
      * modify attribute and include stacking tests
      
      * backwards compatibility
      
      * check sklearn version
      
      * move stacking import
      
      * Number of input features (#3173)
      
      * Number of input features (#3173)
      
      * Number of input features (#3173)
      
      * Number of input features (#3173)
      
      Split number of features and stacking tests.
      
      * Number of input features (#3173)
      
      Modify test name.
      
      * Number of input features (#3173)
      
      Update stacking tests for review comments.
      
      * Number of input features (#3173)
      
      * Number of input features (#3173)
      
      * Number of input features (#3173)
      
      * Number of input features (#3173)
      
      Modify classifier test.
      
      * Number of input features (#3173)
      
      * Number of input features (#3173)
      
      Check score.
      72849466
  5. 23 Jun, 2020 1 commit
    • Belinda Trotta's avatar
      Interaction constraints (#3126) · bca2da97
      Belinda Trotta authored
      * Add interaction constraints functionality.
      
      * Minor fixes.
      
      * Minor fixes.
      
      * Change lambda to function.
      
      * Fix gpu bug, remove extra blank lines.
      
      * Fix gpu bug.
      
      * Fix style issues.
      
      * Try to fix segfault on MACOS.
      
      * Fix bug.
      
      * Fix bug.
      
      * Fix bugs.
      
      * Change parameter format for R.
      
      * Fix R style issues.
      
      * Change string formatting code.
      
      * Change docs to say R package not supported.
      
      * Remove R functionality, moving to separate PR.
      
      * Keep track of branch features in tree object.
      
      * Only track branch features when feature interactions are enabled.
      
      * Fix lint error.
      
      * Update docs and simplify tests.
      bca2da97
  6. 22 Jun, 2020 1 commit
  7. 11 Jun, 2020 1 commit
  8. 02 Jun, 2020 1 commit
  9. 20 May, 2020 1 commit
  10. 12 May, 2020 1 commit
  11. 09 May, 2020 1 commit
  12. 05 May, 2020 1 commit
  13. 13 Apr, 2020 1 commit
  14. 10 Apr, 2020 2 commits
  15. 20 Mar, 2020 2 commits
    • Alberto Ferreira's avatar
      Fix SWIG methods that return char** (#2850) · 91185c3a
      Alberto Ferreira authored
      
      
      * [swig] Fix SWIG methods that return char** with StringArray.
      
      + [new] Add StringArray class to manage and manipulate arrays of fixed-length strings:
      
        This class is now used to wrap any char** parameters, manage memory and
        manipulate the strings.
      
        Such class is defined at swig/StringArray.hpp and wrapped in StringArray.i.
      
      + [API+fix] Wrap LGBM_BoosterGetFeatureNames it resulted in segfault before:
      
        Added wrapper LGBM_BoosterGetFeatureNamesSWIG(BoosterHandle) that
        only receives the booster handle and figures how much memory to allocate
        for strings and returns a StringArray which can be easily converted to String[].
      
      + [API+safety] For consistency, LGBM_BoosterGetEvalNamesSWIG was wrapped as well:
      
        * Refactor to detect any kind of errors and removed all the parameters
          besides the BoosterHandle (much simpler API to use in Java).
        * No assumptions are made about the required string space necessary (128 before).
        * The amount of required string memory is computed internally
      
      + [safety] No possibility of undefined behaviour
      
        The two methods wrapped above now compute the necessary string storage space
        prior to allocation, as the low-level C API calls would crash the process
        irreversibly if they write more memory than which is passed to them.
      
      * Changes to C API and wrappers support char**
      
      To support the latest SWIG changes that enable proper char**
      return support that is safe, the C API was changed.
      
      The respecive wrappers in R and Python were changed too.
      
      * Cleanup indentation in new lightgbm_R.cpp code
      
      * Adress review code-style comments.
      
      * Update swig/StringArray.hpp
      Co-Authored-By: default avatarNikita Titov <nekit94-08@mail.ru>
      
      * Update python-package/lightgbm/basic.py
      Co-Authored-By: default avatarNikita Titov <nekit94-08@mail.ru>
      
      * Update src/lightgbm_R.cpp
      Co-Authored-By: default avatarNikita Titov <nekit94-08@mail.ru>
      Co-authored-by: default avataralberto.ferreira <alberto.ferreira@feedzai.com>
      Co-authored-by: default avatarNikita Titov <nekit94-08@mail.ru>
      91185c3a
    • Lukas Pfannschmidt's avatar
      [python] handle RandomState object in Scikit-learn Api (#2904) · cf0a992e
      Lukas Pfannschmidt authored
      
      
      * Add handling of RandomState object, which is standard for sklearn methods.
      
      LightGBM expects an integer seed instead of an object.
      If passed object is RandomState, we choose random integer based on its state to seed the underlying low level code.
      While chosen random integer is only in the range between 1 and 1e10 I expect it to have enough entropy (?) to not matter in practice.
      
      * Add RandomState object to random_state docstring.
      
      * remove blank line
      
      * Use property to handle setting random_state.
      This enables setting cloned estimators with the set_params method in sklearn.
      
      * Add docstring to attribute.
      
      * Fix and simplify docstring.
      
      * Add test case.
      
      * Use maximal int for datatype in seed derivation.
      
      * Replace random_state property with interfacing in fit method.
      Derives int seed for C code only when fitting and keeps RandomState object as param.
      
      * Adapt unit test to property change.
      
      * Extended test case and docstring
      Co-Authored-By: default avatarNikita Titov <nekit94-08@mail.ru>
      
      * Add more equality checks (feature importance, best iteration/score).
      
      * Add equality comparison of boosters represented by strings.
      Remove useless best_iteration_ comparison (we do not use early_stopping).
      
      * fix whitespace
      
      * Test if two subsequent fits produce different models
      
      * Apply suggestions from code review
      Co-Authored-By: default avatarNikita Titov <nekit94-08@mail.ru>
      Co-authored-by: default avatarNikita Titov <nekit94-08@mail.ru>
      cf0a992e
  16. 16 Mar, 2020 2 commits
  17. 06 Mar, 2020 1 commit
  18. 26 Feb, 2020 1 commit
  19. 20 Feb, 2020 1 commit
    • Joan Fontanals's avatar
      Add capability to get possible max and min values for a model (#2737) · 18e7de4f
      Joan Fontanals authored
      
      
      * Add capability to get possible max and min values for a model
      
      * Change implementation to have return value in tree.cpp, change naming to upper and lower bound, move implementation to gdbt.cpp
      
      * Update include/LightGBM/c_api.h
      Co-Authored-By: default avatarNikita Titov <nekit94-08@mail.ru>
      
      * Change iteration to avoid potential overflow, add bindings to R and Python and a basic test
      
      * Adjust test values
      
      * Consider const correctness and multithreading protection
      
      * Update test values
      
      * Update test values
      
      * Add test to check that model is exactly the same in all platforms
      
      * Try to parse the model to get the expected values
      
      * Try to parse the model to get the expected values
      
      * Fix implementation, num_leaves can be lower than the leaf_value_ size
      
      * Do not check for num_leaves to be smaller than actual size and get back to test with hardcoded value
      
      * Change test order
      
      * Add gpu_use_dp option in test
      
      * Remove helper test method
      
      * Update src/c_api.cpp
      Co-Authored-By: default avatarNikita Titov <nekit94-08@mail.ru>
      
      * Update src/io/tree.cpp
      Co-Authored-By: default avatarNikita Titov <nekit94-08@mail.ru>
      
      * Update src/io/tree.cpp
      Co-Authored-By: default avatarNikita Titov <nekit94-08@mail.ru>
      
      * Update tests/python_package_test/test_basic.py
      Co-Authored-By: default avatarNikita Titov <nekit94-08@mail.ru>
      
      * Remoove imports
      Co-authored-by: default avatarNikita Titov <nekit94-08@mail.ru>
      18e7de4f
  20. 19 Feb, 2020 1 commit
    • Guolin Ke's avatar
      [python] [R-package] refine the parameters for Dataset (#2594) · 9f79e840
      Guolin Ke authored
      
      
      * reset
      
      * fix a bug
      
      * fix test
      
      * Update c_api.h
      
      * support to no filter features by min_data
      
      * add warning in reset config
      
      * refine warnings for override dataset's parameter
      
      * some cleans
      
      * clean code
      
      * clean code
      
      * refine C API function doxygen comments
      
      * refined new param description
      
      * refined doxygen comments for R API function
      
      * removed stuff related to int8
      
      * break long line in warning message
      
      * removed tests which results cannot be validated anymore
      
      * added test for warnings about unchangeable params
      
      * write parameter from dataset to booster
      
      * consider free_raw_data.
      
      * fix params
      
      * fix bug
      
      * implementing R
      
      * fix typo
      
      * filter params in R
      
      * fix R
      
      * not min_data
      
      * refined tests
      
      * fixed linting
      
      * refine
      
      * pilint
      
      * add docstring
      
      * fix docstring
      
      * R lint
      
      * updated description for C API function
      
      * use param aliases in Python
      
      * fixed typo
      
      * fixed typo
      
      * added more params to test
      
      * removed debug print
      
      * fix dataset construct place
      
      * fix merge bug
      
      * Update feature_histogram.hpp
      
      * add is_sparse back
      
      * remove unused parameters
      
      * fix lint
      
      * add data random seed
      
      * update
      
      * [R-package] centrallized Dataset parameter aliases and added tests on Dataset parameter updating (#2767)
      Co-authored-by: default avatarNikita Titov <nekit94-08@mail.ru>
      Co-authored-by: default avatarJames Lamb <jaylamb20@gmail.com>
      9f79e840
  21. 15 Feb, 2020 1 commit
  22. 06 Feb, 2020 1 commit
  23. 03 Feb, 2020 2 commits
  24. 16 Jan, 2020 1 commit
  25. 14 Jan, 2020 2 commits
  26. 12 Jan, 2020 1 commit
  27. 10 Jan, 2020 1 commit
    • Patrick Ford's avatar
      [python] Output model to a pandas DataFrame (#2592) · 301402c8
      Patrick Ford authored
      * trees_to_df method and unit test added. PEP 8 fixes for integration.
      
      * Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>
      
      Post-review changes
      
      * changes from second round of reviews from striker
      
      * third round of review. formatting and added 2 more tests
      
      * replaced pandas dot attribute accessor with string attribute accessor
      
      * dealt with single tree edge case and minor refactor of tests
      
      * slight refactor for checking if tree is a single node
      301402c8
  28. 02 Jan, 2020 1 commit
  29. 29 Dec, 2019 1 commit
  30. 19 Dec, 2019 1 commit
  31. 09 Dec, 2019 1 commit
  32. 08 Dec, 2019 1 commit
  33. 05 Dec, 2019 2 commits
  34. 27 Oct, 2019 1 commit