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\r\nRelease notes\r\n

Sourced from catboost's\r\nreleases.

\r\n
\r\n

1.2.3

\r\n

Python package

\r\n
    \r\n
  • Support Python 3.12. #2510
    • \r\n
  • [Performance]: Fix ineffective loops in Cython. Significant speedups\r\n(up to 3x) on dataset construction from data in C-order can be\r\nexpected.
    • \r\n
  • [Performance]: Make features data initialization from C-order\r\nnumpy.ndarrays with float32 data type\r\nmultithreaded. Significant speedups of 5x up to 10x (on CPUs with many\r\ncores) can be expected. #385,\r\n#2542
    • \r\n
  • Save training metrics into the model metadata. So\r\nbest_score_, evals_result_,\r\nbest_iteration_ model attributes now work after model\r\nsaving and loading. Can be removed by model metadata manipulation if\r\nneeded. #1166
    • \r\n
  • [Breaking change]. Support a separate boolean target type, now\r\nClass predictions for models that have been trained with\r\nboolean targets will also be boolean instead of True,\r\nFalse strings as before. Such models will be incompatible\r\nwith the previous versions of CatBoost appliers. If you want the old\r\nbehavior convert your target to False, True\r\nstrings before training. #1954
    • \r\n
  • Restrict jupyterlab version for setup to 3.x for now.\r\nFixes #2530
    • \r\n
  • utils.read_cd: Support CD files with non-increasing\r\ncolumn indices.
    • \r\n
  • Make log_cout, log_cerr specification\r\nconsistent, avoid reset in recursive calls.
    • \r\n
  • Late-initialize default values for log_cout,\r\nlog_cerr. #2195
    • \r\n
  • Add missing generated metrics: Cox,\r\nPairLogitPairwise, UserPerObjMetric,\r\nSurvivalAft.
    • \r\n
\r\n

New features

\r\n
    \r\n
  • Support boolean target/labels type during training in Python and\r\nSpark (in the latter case only when using fit with\r\nPool arguments) and Class prediction in\r\nPython. #1954
    • \r\n
  • [Spark]: Support Spark 3.5.x.
    • \r\n
  • [C/C++ applier]. Add functions for getting indices of features of\r\ndifferent types to C and C++ API. #2568.\r\nThanks to @​nimusp.
    • \r\n
  • [C/C++ applier]. Add staged prediction functions to C API. #2584.\r\nThanks to @​Mb-NextTime.
    • \r\n
  • [JVM applier]. Add loading CatBoostModel from a byte array to API.\r\n#2539
    • \r\n
  • [Linux] Support CgroupsV2 when computing default number of threads\r\nused in parallel computations. #2519.\r\nThanks to @​elukey.
    • \r\n
  • [CLI] Support printing Auxiliary columns by name in\r\nevaluation result output. #1659
    • \r\n
  • Save training metrics into the model metadata. Can be removed by\r\nmodel metadata manipulation if needed. #1166
    • \r\n
\r\n

Build & testing

\r\n
    \r\n
  • [Windows]: Use clang-cl compiler and tools from Visual\r\nStudio 2022 for the build without CUDA (build with CUDA still uses\r\nstandard Microsoft toolchain from Visual Studio 2019).
    • \r\n
  • [macOS]: Pass os.version to conan host\r\nsettings to ensure version consistency.
    • \r\n
  • [Linux aarch64]: Set -mno-outline-atomics for modern\r\nversions of CLang and GCC to avoid unresolved symbols linking errors. #2527
    • \r\n
  • Added missing CMakeLists for unit tests for\r\nutil. #2525
    • \r\n
\r\n

Bugfixes

\r\n
    \r\n
  • [Performance]: Fix performance regression that could slow down\r\ntraining on GPU by 50% on some datasets that had been introduced in\r\nrelease 1.2. Thanks to @​JeanPaulShapo.
    • \r\n
  • [Python-package]: Fix segfault on Pool(data=None). #2522
    • \r\n
  • [Python-package]: Fix Python exception in Pool() when\r\npairs_weight is a numpy array. #1913
    • \r\n
  • [Python-package]: Fix segfault and other strange errors when\r\nspecifying custom logger with __call__ method. #2277
    • \r\n
  • [Python-package]: Fix returning complex params in hyperparameter\r\nsearch. #1741,\r\n#1833
    • \r\n
  • [Python-package]: Fix ignored exceptions for missed metrics\r\ndescriptions on startup. This has not been visible to users but has been\r\nmaking debugging more difficult.
    • \r\n
  • [Python-package]: Fix misleading Targets are required for\r\nYetiRank loss function. error in Cross validation. #2083
    • \r\n
  • [Python-package]: Fix Pool.get_label() returns constant\r\nTrue for boolean labels. #2133
    • \r\n
  • [Python-package]: Copying models does not lose\r\nbest_score_, evals_result_,\r\nbest_iteration_ attributes values anymore. #1793
    • \r\n
  • [Spark]: Fix hangs at the end of the training. #2151
    • \r\n
  • Precision metric default value in the absense of\r\npositive samples is changed to 0 and a warning is added\r\n(similar to the behavior of scikit-learn implementation).\r\n#2422
    • \r\n
  • Fix ignoring embedding features
    • \r\n
  • Try to avoid hash collisions when computing group ids with datasets\r\nwith a lot of groups (may occur in datasets with around a 10^9\r\nsamples).
    • \r\n
  • Fix Multiclass models export to C++ and Python code. #2549
    • \r\n
  • Fix dataset_statistics mode when no Target data is\r\navailable.
    • \r\n
  • Fix Error: can't proceed some features error on GPU. #1024
    • \r\n
  • Fix allow_const_label=True for classification. #1933
    • \r\n
  • Add checking of approx and target dimensions for\r\nSurvivalAft objective/metric.
    • \r\n
  • Fix Focal loss derivatives sign. #2563
    • \r\n
\r\n
\r\n
\r\n
\r\nChangelog\r\n

Sourced from catboost's\r\nchangelog.

\r\n
\r\n

Release 1.2.3

\r\n

Python package

\r\n
    \r\n
  • Support Python 3.12. #2510
    • \r\n
  • [Performance]: Fix ineffective loops in Cython. Significant speedups\r\n(up to 3x) on dataset construction from data in C-order can be\r\nexpected.
    • \r\n
  • [Performance]: Make features data initialization from C-order\r\nnumpy.ndarrays with float32 data type\r\nmultithreaded. Significant speedups of 5x up to 10x (on CPUs with many\r\ncores) can be expected. #385,\r\n#2542
    • \r\n
  • Save training metrics into the model metadata. So\r\nbest_score_, evals_result_,\r\nbest_iteration_ model attributes now work after model\r\nsaving and loading. Can be removed by model metadata manipulation if\r\nneeded. #1166
    • \r\n
  • [Breaking change]. Support a separate boolean target type, now\r\nClass predictions for models that have been trained with\r\nboolean targets will also be boolean instead of True,\r\nFalse strings as before. Such models will be incompatible\r\nwith the previous versions of CatBoost appliers. If you want the old\r\nbehavior convert your target to False, True\r\nstrings before training. #1954
    • \r\n
  • Restrict jupyterlab version for setup to 3.x for now.\r\nFixes #2530
    • \r\n
  • utils.read_cd: Support CD files with non-increasing\r\ncolumn indices.
    • \r\n
  • Make log_cout, log_cerr specification\r\nconsistent, avoid reset in recursive calls.
    • \r\n
  • Late-initialize default values for log_cout,\r\nlog_cerr. #2195
    • \r\n
  • Add missing generated metrics: Cox,\r\nPairLogitPairwise, UserPerObjMetric,\r\nSurvivalAft.
    • \r\n
\r\n

New features

\r\n
    \r\n
  • Support boolean target/labels type during training in Python and\r\nSpark (in the latter case only when using fit with\r\nPool arguments) and Class prediction in\r\nPython. #1954
    • \r\n
  • [Spark]: Support Spark 3.5.x.
    • \r\n
  • [C/C++ applier]. Add functions for getting indices of features of\r\ndifferent types to C and C++ API. #2568.\r\nThanks to @​nimusp.
    • \r\n
  • [C/C++ applier]. Add staged prediction functions to C API. #2584.\r\nThanks to @​Mb-NextTime.
    • \r\n
  • [JVM applier]. Add loading CatBoostModel from a byte array to API.\r\n#2539
    • \r\n
  • [Linux] Support CgroupsV2 when computing default number of threads\r\nused in parallel computations. #2519.\r\nThanks to @​elukey.
    • \r\n
  • [CLI] Support printing Auxiliary columns by name in\r\nevaluation result output. #1659
    • \r\n
  • Save training metrics into the model metadata. Can be removed by\r\nmodel metadata manipulation if needed. #1166
    • \r\n
\r\n

Build & testing

\r\n
    \r\n
  • [Windows]: Use clang-cl from Visual Studio 2022 for the\r\nbuild without CUDA (build with CUDA still uses standard Microsoft\r\ntoolchain from Visual Studio 2019).
    • \r\n
  • [macOS]: Pass os.version to conan host\r\nsettings to ensure version consistency.
    • \r\n
  • [Linux aarch64]: Set -mno-outline-atomics for modern\r\nversions of CLang and GCC to avoid unresolved symbols linking errors. #2527
    • \r\n
  • Added missing CMakeLists for unit tests for\r\nutil. #2525
    • \r\n
\r\n

Bugfixes

\r\n
    \r\n
  • [Performance]: Fix performance regression that could slow down\r\ntraining on GPU by 50% on some datasets that had been introduced in\r\nrelease 1.2. Thanks to @​JeanPaulShapo.
    • \r\n
  • [Python-package]: Fix segfault on Pool(data=None). #2522
    • \r\n
  • [Python-package]: Fix Python exception in Pool() when\r\npairs_weight is a numpy array. #1913
    • \r\n
  • [Python-package]: Fix segfault and other strange errors when\r\nspecifying custom logger with __call__ method. #2277
    • \r\n
  • [Python-package]: Fix returning complex params in hyperparameter\r\nsearch. #1741,\r\n#1833
    • \r\n
  • [Python-package]: Fix ignored exceptions for missed metrics\r\ndescriptions on startup. This has not been visible to users but has been\r\nmaking debugging more difficult.
    • \r\n
  • [Python-package]: Fix misleading Targets are required for\r\nYetiRank loss function. error in Cross validation. #2083
    • \r\n
  • [Python-package]: Fix Pool.get_label() returns constant\r\nTrue for boolean labels. #2133
    • \r\n
  • [Python-package]: Copying models does not lose\r\nbest_score_, evals_result_,\r\nbest_iteration_ attributes values anymore. #1793
    • \r\n
  • [Spark]: Fix hangs at the end of the training. #2151
    • \r\n
  • Precision metric default value in the absense of\r\npositive samples is changed to 0 and a warning is added\r\n(similar to the behavior of scikit-learn implementation).\r\n#2422
    • \r\n
  • Fix ignoring embedding features
    • \r\n
  • Try to avoid hash collisions when computing group ids with datasets\r\nwith a lot of groups (may occur in datasets with around a 10^9\r\nsamples).
    • \r\n
  • Fix Multiclass models export to C++ and Python code. #2549
    • \r\n
  • Fix dataset_statistics mode when no Target data is\r\navailable.
    • \r\n
  • Fix Error: can't proceed some features error on GPU. #1024
    • \r\n
  • Fix allow_const_label=True for classification. #1933
    • \r\n
  • Add checking of approx and target dimensions for\r\nSurvivalAft objective/metric.
    • \r\n
\r\n\r\n
\r\n

... (truncated)

\r\n
\r\n
\r\nCommits\r\n
    \r\n
  • fe0941b\r\nUse paths from CMAKE_*_DIR when running in open source to avoid issues\r\non Win...
    • \r\n
  • cf282f7\r\nCatBoost release 1.2.3.
    • \r\n
  • ec263e7\r\nUpdate contrib/python/ipywidgets/py3 to 8.1.2
    • \r\n
  • 704a5d8\r\nIntermediate changes
    • \r\n
  • a13b5ba\r\nAdd loading CatBoostModel from a byte array to API.. Fix #2539
    • \r\n
  • 56a0b44\r\nAdd Get*FeaturesIndices to C++ wrapper. #2323,\r\n#2568
    • \r\n
  • caed72b\r\nAdd GetEmbeddingFeaturesCount() to C++ wrapper
    • \r\n
  • 4490314\r\nAdd Spark 3.5 to pyspark_wrapper_generator.
    • \r\n
  • 98c3667\r\nSupport boolean target type in Spark (where possible).
    • \r\n
  • ad980da\r\nManually unroll the loop
    • \r\n
  • Additional commits viewable in compare\r\nview
    • \r\n
\r\n
\r\n
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