1. 11 Oct, 2025 1 commit
  2. 18 Oct, 2024 1 commit
  3. 10 Oct, 2023 1 commit
  4. 09 Oct, 2023 1 commit
  5. 03 Aug, 2022 1 commit
  6. 29 Jul, 2022 1 commit
  7. 05 Apr, 2021 1 commit
  8. 18 Jan, 2021 1 commit
    • James Lamb's avatar
      [R-package] enable use of trees with linear models at leaves (fixes #3319) (#3699) · ed651e86
      James Lamb authored
      * [R-package] enable use of trees with linear models at leaves (fixes #3319)
      
      * remove problematic pragmas
      
      * fix tests
      
      * try to fix build scripts
      
      * try fixing pragma check
      
      * more pragma checks
      
      * ok fix pragma stuff for real
      
      * empty commit
      
      * regenerate documentation
      
      * try skipping test
      
      * uncomment CI
      
      * add note on missing value types for R
      
      * add tests on saving and re-loading booster
      ed651e86
  9. 11 Jan, 2021 1 commit
  10. 07 Jan, 2021 1 commit
  11. 29 Dec, 2020 1 commit
  12. 28 Dec, 2020 1 commit
    • Nikita Titov's avatar
      small code and docs refactoring (#3681) · 5a460846
      Nikita Titov authored
      * small code and docs refactoring
      
      * Update CMakeLists.txt
      
      * Update .vsts-ci.yml
      
      * Update test.sh
      
      * continue
      
      * continue
      
      * revert stable sort for all-unique values
      5a460846
  13. 24 Dec, 2020 1 commit
    • Belinda Trotta's avatar
      Trees with linear models at leaves (#3299) · fcfd4132
      Belinda Trotta authored
      * Add Eigen library.
      
      * Working for simple test.
      
      * Apply changes to config params.
      
      * Handle nan data.
      
      * Update docs.
      
      * Add test.
      
      * Only load raw data if boosting=gbdt_linear
      
      * Remove unneeded code.
      
      * Minor updates.
      
      * Update to work with sk-learn interface.
      
      * Update to work with chunked datasets.
      
      * Throw error if we try to create a Booster with an already-constructed dataset having incompatible parameters.
      
      * Save raw data in binary dataset file.
      
      * Update docs and fix parameter checking.
      
      * Fix dataset loading.
      
      * Add test for regularization.
      
      * Fix bugs when saving and loading tree.
      
      * Add test for load/save linear model.
      
      * Remove unneeded code.
      
      * Fix case where not enough leaf data for linear model.
      
      * Simplify code.
      
      * Speed up code.
      
      * Speed up code.
      
      * Simplify code.
      
      * Speed up code.
      
      * Fix bugs.
      
      * Working version.
      
      * Store feature data column-wise (not fully working yet).
      
      * Fix bugs.
      
      * Speed up.
      
      * Speed up.
      
      * Remove unneeded code.
      
      * Small speedup.
      
      * Speed up.
      
      * Minor updates.
      
      * Remove unneeded code.
      
      * Fix bug.
      
      * Fix bug.
      
      * Speed up.
      
      * Speed up.
      
      * Simplify code.
      
      * Remove unneeded code.
      
      * Fix bug, add more tests.
      
      * Fix bug and add test.
      
      * Only store numerical features
      
      * Fix bug and speed up using templates.
      
      * Speed up prediction.
      
      * Fix bug with regularisation
      
      * Visual studio files.
      
      * Working version
      
      * Only check nans if necessary
      
      * Store coeff matrix as an array.
      
      * Align cache lines
      
      * Align cache lines
      
      * Preallocation coefficient calculation matrices
      
      * Small speedups
      
      * Small speedup
      
      * Reverse cache alignment changes
      
      * Change to dynamic schedule
      
      * Update docs.
      
      * Refactor so that linear tree learner is not a separate class.
      
      * Add refit capability.
      
      * Speed up
      
      * Small speedups.
      
      * Speed up add prediction to score.
      
      * Fix bug
      
      * Fix bug and speed up.
      
      * Speed up dataload.
      
      * Speed up dataload
      
      * Use vectors instead of pointers
      
      * Fix bug
      
      * Add OMP exception handling.
      
      * Change return type of LGBM_BoosterGetLinear to bool
      
      * Change return type of LGBM_BoosterGetLinear back to int, only parameter type needed to change
      
      * Remove unused internal_parent_ property of tree
      
      * Remove unused parameter to CreateTreeLearner
      
      * Remove reference to LinearTreeLearner
      
      * Minor style issues
      
      * Remove unneeded check
      
      * Reverse temporary testing change
      
      * Fix Visual Studio project files
      
      * Restore LightGBM.vcxproj.filters
      
      * Speed up
      
      * Speed up
      
      * Simplify code
      
      * Update docs
      
      * Simplify code
      
      * Initialise storage space for max num threads
      
      * Move Eigen to include directory and delete unused files
      
      * Remove old files.
      
      * Fix so it compiles with mingw
      
      * Fix gpu tree learner
      
      * Change AddPredictionToScore back to const
      
      * Fix python lint error
      
      * Fix C++ lint errors
      
      * Change eigen to a submodule
      
      * Update comment
      
      * Add the eigen folder
      
      * Try to fix build issues with eigen
      
      * Remove eigen files
      
      * Add eigen as submodule
      
      * Fix include paths
      
      * Exclude eigen files from Python linter
      
      * Ignore eigen folders for pydocstyle
      
      * Fix C++ linting errors
      
      * Fix docs
      
      * Fix docs
      
      * Exclude eigen directories from doxygen
      
      * Update manifest to include eigen
      
      * Update build_r to include eigen files
      
      * Fix compiler warnings
      
      * Store raw feature data as float
      
      * Use float for calculating linear coefficients
      
      * Remove eigen directory from GLOB
      
      * Don't compile linear model code when building R package
      
      * Fix doxygen issue
      
      * Fix lint issue
      
      * Fix lint issue
      
      * Remove uneeded code
      
      * Restore delected lines
      
      * Restore delected lines
      
      * Change return type of has_raw to bool
      
      * Update docs
      
      * Rename some variables and functions for readability
      
      * Make tree_learner parameter const in AddScore
      
      * Fix style issues
      
      * Pass vectors as const reference when setting tree properties
      
      * Make temporary storage of serial_tree_learner mutable so we can make the object's methods const
      
      * Remove get_raw_size, use num_numeric_features instead
      
      * Fix typo
      
      * Make contains_nan_ and any_nan_ properties immutable again
      
      * Remove data_has_nan_ property of tree
      
      * Remove temporary test code
      
      * Make linear_tree a dataset param
      
      * Fix lint error
      
      * Make LinearTreeLearner a separate class
      
      * Fix lint errors
      
      * Fix lint error
      
      * Add linear_tree_learner.o
      
      * Simulate omp_get_max_threads if openmp is not available
      
      * Update PushOneData to also store raw data.
      
      * Cast size to int
      
      * Fix bug in ReshapeRaw
      
      * Speed up code with multithreading
      
      * Use OMP_NUM_THREADS
      
      * Speed up with multithreading
      
      * Update to use ArrayToString
      
      * Fix tests
      
      * Fix test
      
      * Fix bug introduced in merge
      
      * Minor updates
      
      * Update docs
      fcfd4132