Repository Analysis

dmlc/xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

6.4 Low AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of dmlc/xgboost, a C++ project with 28,558 GitHub stars. SynthScan v2.0 examined 144,671 lines of code across 761 source files, recording 824 pattern matches distributed across 18 syntactic categories. The overall adjusted score of 6.4 places this repository in the Low AI signal band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

6.4
Adjusted Score
6.4
Raw Score
100%
Time Factor
2026-07-14
Last Push
28.6K
Stars
C++
Language
144.7K
Lines of Code
761
Files
824
Pattern Hits
2026-07-14
Scan Date
0.01
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 4HIGH 6MEDIUM 17LOW 797

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 824 distinct pattern matches across 18 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Hyper-Verbose Identifiers285 hits · 308 pts
SeverityFileLineSnippetContext
LOWdemo/dask/gpu_training.py42def using_quantile_device_dmatrix(client: Client, X: da.Array, y: da.Array) -> da.Array:CODE
LOWdemo/dask/dask_callbacks.py18def probability_for_going_backward(epoch: int) -> float:CODE
LOWdemo/nvflare/horizontal/custom/controller.py48 def process_result_of_unknown_task(self, client: Client, task_name: str,CODE
LOWdemo/nvflare/vertical/custom/controller.py48 def process_result_of_unknown_task(self, client: Client, task_name: str,CODE
LOWdemo/guide-python/continuation.py50def training_continuation_early_stop(tmpdir: str, use_pickle: bool) -> None:CODE
LOWdemo/guide-python/prediction_intervals.py138def plot_prediction_intervals(CODE
LOWtests/python/test_ordinal.py72def test_training_continuation() -> None:CODE
LOWtests/python/test_ordinal.py80def test_recode_dmatrix_predict() -> None:CODE
LOWtests/python/test_training_continuation.py37 def run_training_continuation(CODE
LOWtests/python/test_training_continuation.py134 def test_training_continuation_json(self, tmp_path: Path) -> None:CODE
LOWtests/python/test_training_continuation.py139 def test_training_continuation_updaters_json(self, tmp_path: Path) -> None:CODE
LOWtests/python/test_training_continuation.py174def test_continuation_determinism(kwargs: Any) -> None:CODE
LOWtests/python/test_basic.py191 def test_dmatrix_numpy_init_omp(self):CODE
LOWtests/python/test_basic.py227 def test_cv_explicit_fold_indices(self):CODE
LOWtests/python/test_basic.py241 def test_cv_explicit_fold_indices_labels(self):CODE
LOWtests/python/test_early_stopping.py15 def test_early_stopping_nonparallel(self):CODE
LOWtests/python/test_early_stopping.py122 def test_cv_early_stopping_with_multiple_eval_sets_and_metrics(self):CODE
LOWtests/python/test_with_arrow.py39 def test_arrow_table_with_label(self):CODE
LOWtests/python/test_data_iterator.py337def test_categorical_extmem_qdm(CODE
LOWtests/python/test_interaction_constraints.py10 def test_exact_interaction_constraints(self) -> None:CODE
LOWtests/python/test_interaction_constraints.py13 def test_hist_interaction_constraints(self) -> None:CODE
LOWtests/python/test_interaction_constraints.py16 def test_approx_interaction_constraints(self) -> None:CODE
LOWtests/python/test_interaction_constraints.py19 def test_hist_multi_interaction_constraints(self) -> None:CODE
LOWtests/python/test_interaction_constraints.py22 def test_interaction_constraints_feature_names(self) -> None:CODE
LOWtests/python/test_interaction_constraints.py59 def test_hist_training_accuracy(self, tree_method: str) -> None:CODE
LOWtests/python/test_model_io.py104 def test_categorical_model_io(self, tmp_path: Path) -> None:CODE
LOWtests/python/test_model_io.py341def test_with_sklearn_obj_metric(tmp_path: Path) -> None:CODE
LOWtests/python/generate_models.py37def generate_regression_model() -> None:CODE
LOWtests/python/generate_models.py107def generate_classification_model() -> None:CODE
LOWtests/python/generate_models.py178def generate_aft_survival_models() -> None:CODE
LOWtests/python/test_callback.py124 def test_early_stopping_custom_eval(self, breast_cancer: BreastCancer) -> None:CODE
LOWtests/python/test_callback.py144 def test_early_stopping_customize(self, breast_cancer: BreastCancer) -> None:CODE
LOWtests/python/test_callback.py206 def test_early_stopping_custom_eval_skl(self, breast_cancer: BreastCancer) -> None:CODE
LOWtests/python/test_callback.py218 def test_early_stopping_save_best_model(self, breast_cancer: BreastCancer) -> None:CODE
LOWtests/python/test_callback.py258 def test_early_stopping_continuation(CODE
LOWtests/python/test_callback.py292 def test_early_stopping_multiple_metrics(self):CODE
LOWtests/python/test_callback.py314 def test_eta_decay_leaf_output(self, tree_method: str, objective: str) -> None:CODE
LOWtests/python/test_basic_models.py104 def test_boost_from_prediction(self):CODE
LOWtests/python/test_basic_models.py119 def test_boost_from_existing_model(self) -> None:CODE
LOWtests/python/test_basic_models.py227 def test_feature_names_validation(self):CODE
LOWtests/python/test_basic_models.py243 def test_special_model_dump_characters(self) -> None:CODE
LOWtests/python/test_survival.py58def test_aft_survival_toy_data(CODE
LOWtests/python/test_survival.py133def test_aft_survival_demo_data():CODE
LOWtests/python/test_dmatrix.py413 def verify_numpy_feature_names():CODE
LOWtests/python/test_predict.py74def test_base_margin_vs_base_score() -> None:CODE
LOWtests/python/test_ranking.py93def test_ranking_with_unweighted_data():CODE
LOWtests/python/test_ranking.py127def test_ranking_with_weighted_data():CODE
LOWtests/python/test_ranking.py184def test_lambdarank_parameters(params):CODE
LOWtests/python/test_multi_target.py46def test_shap_multi_output_tree() -> None:CODE
LOWtests/python/test_multi_target.py196def test_feature_importance_strategy_compare() -> None:CODE
LOWtests/python/test_multi_target.py210def test_gradient_based_sampling_accuracy() -> None:CODE
LOWtests/python/test_interpret.py7def test_shap_values_matches_predict() -> None:CODE
LOWtests/python/test_interpret.py20def test_shap_values_accepts_sklearn_model() -> None:CODE
LOWtests/python/test_interpret.py34def test_shap_values_uses_sklearn_iteration_range() -> None:CODE
LOWtests/python/test_interpret.py51def test_shap_values_rejects_background_data() -> None:CODE
LOWtests/python/test_interpret.py61def test_shap_values_validates_get_booster() -> None:CODE
LOWtests/python/test_interpret.py69def test_shap_values_uses_missing_for_array_like_data() -> None:CODE
LOWtests/python/test_interpret.py83def test_shap_values_rejects_missing_with_dmatrix() -> None:CODE
LOWtests/python/test_config.py10def test_global_config_verbosity(verbosity_level):CODE
LOWtests/python/test_config.py23def test_global_config_use_rmm(use_rmm):CODE
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Over-Commented Block320 hits · 300 pts
SeverityFileLineSnippetContext
LOWdemo/kaggle-higgs/speedtest.R41 nrounds <- 120COMMENT
LOWdemo/kaggle-higgs/speedtest.R61# 111.682 0.777 35.963COMMENT
LOWdemo/guide-python/generalized_linear_model.py21# alpha is the L1 regularizerCOMMENT
LOWR-package/R/xgb.DMatrix.save.R1#' Save xgb.DMatrix object to binary fileCOMMENT
LOWR-package/R/xgb.plot.multi.trees.R1#' Project all trees on one treeCOMMENT
LOWR-package/R/xgb.plot.multi.trees.R21#'COMMENT
LOWR-package/R/xgb.plot.multi.trees.R41#' nrounds = 30,COMMENT
LOWR-package/R/xgb.plot.deepness.R1#' Plot model tree depthCOMMENT
LOWR-package/R/xgb.plot.deepness.R21#' Those could be helpful in determining sensible ranges of the `max_depth`COMMENT
LOWR-package/R/xgb.plot.deepness.R41#'COMMENT
LOWR-package/R/xgb.plot.deepness.R61#' xgb.plot.deepness(model)COMMENT
LOWR-package/R/utils.R381COMMENT
LOWR-package/R/utils.R421#' for objects produced by [xgboost()]), outside of its core components, might also keep:COMMENT
LOWR-package/R/utils.R441#' not used for prediction / importance / plotting / etc.COMMENT
LOWR-package/R/utils.R461#' preferred for long-term storage.COMMENT
LOWR-package/R/utils.R481#'COMMENT
LOWR-package/R/utils.R501#' xgb.save(bst, fname)COMMENT
LOWR-package/R/utils.R521#' obj2 <- readRDS(fname)COMMENT
LOWR-package/R/utils.R541#' that code calling xgboost will still work once those are removed in future releases.COMMENT
LOWR-package/R/xgb.plot.importance.R1#' Plot feature importanceCOMMENT
LOWR-package/R/xgb.plot.importance.R21#'COMMENT
LOWR-package/R/xgb.plot.importance.R41#' - `xgb.ggplot.importance()`: A customizable "ggplot" object.COMMENT
LOWR-package/R/xgb.plot.importance.R61#' xgb.plot.importance(COMMENT
LOWR-package/R/xgb.plot.importance.R141# Avoid error messages during CRAN check.COMMENT
LOWR-package/R/xgb.save.raw.R1#' Save XGBoost model to R's raw vectorCOMMENT
LOWR-package/R/xgb.save.raw.R21#' train <- agaricus.trainCOMMENT
LOWR-package/R/xgb.plot.shap.R1#' SHAP dependence plotsCOMMENT
LOWR-package/R/xgb.plot.shap.R21#' The default (`NULL`) will use up to 100k data points.COMMENT
LOWR-package/R/xgb.plot.shap.R41#' If `FALSE`, only a list of matrices is returned.COMMENT
LOWR-package/R/xgb.plot.shap.R61#' a meaningful thing to do.COMMENT
LOWR-package/R/xgb.plot.shap.R81#' data.table::setDTthreads(nthread)COMMENT
LOWR-package/R/xgb.plot.shap.R101#'COMMENT
LOWR-package/R/xgb.plot.shap.R121#' model = model_multiclass,COMMENT
LOWR-package/R/xgb.plot.shap.R141#' )COMMENT
LOWR-package/R/xgb.plot.shap.R241#' Visualizes SHAP contributions of different features.COMMENT
LOWR-package/R/xgb.plot.shap.R261#' and the Python library <https://github.com/shap/shap>.COMMENT
LOWR-package/R/xgboost.R821 if (is.na(early_stopping_rounds) || early_stopping_rounds <= 0L) {COMMENT
LOWR-package/R/xgboost.R841#'COMMENT
LOWR-package/R/xgboost.R861#' For package authors using 'xgboost' as a dependency, it is highly recommended to useCOMMENT
LOWR-package/R/xgboost.R881#' Note that categorical features are only supported for `data.frame` inputs, and are automaticallyCOMMENT
LOWR-package/R/xgboost.R901#' set as the last level.COMMENT
LOWR-package/R/xgboost.R921#' prediction type (e.g. `multi:softmax` vs. `multi:softprob`) are not allowed, and neither areCOMMENT
LOWR-package/R/xgboost.R941#' - `"reg:gamma"`: gamma regression with log-link. Output is a mean of gamma distribution. It might be useful, e.g., foCOMMENT
LOWR-package/R/xgboost.R961#' 2 (info), and 3 (debug).COMMENT
LOWR-package/R/xgboost.R981#' @param early_stopping_rounds Number of boosting rounds after which training will be stoppedCOMMENT
LOWR-package/R/xgboost.R1001#' A value of `+1` for a given feature makes the model predictions / scores constrained to beCOMMENT
LOWR-package/R/xgboost.R1021#' for more information.COMMENT
LOWR-package/R/xgboost.R1041#' Note that, if it contains more than one column, then columns will not be matched by name toCOMMENT
LOWR-package/R/xgboost.R1061#' - For linear booster:COMMENT
LOWR-package/R/xgboost.R1081#' @examplesCOMMENT
LOWR-package/R/xgboost.R1101#'COMMENT
LOWR-package/R/xgboost.R1241#'COMMENT
LOWR-package/R/xgboost.R1261#' probabilities of belonging to the last class in the case of binary classification). Result willCOMMENT
LOWR-package/R/xgboost.R1281#' Output will be a numeric matrix with shape `[nrows, nfeatures+1]`, with the intercept being theCOMMENT
LOWR-package/R/xgboost.R1301#' @param iteration_range Sequence of rounds/iterations from the model to use for prediction, specified by passingCOMMENT
LOWR-package/R/xgboost.R1321#'COMMENT
LOWR-package/R/xgboost.R1541 }COMMENT
LOWR-package/R/xgboost.R1561#' School of Information and Computer Science.COMMENT
LOWR-package/R/xgboost.R1581#' <https://archive.ics.uci.edu/ml/datasets/Mushroom>COMMENT
LOWR-package/R/xgboost.R1601#' @importFrom data.table :=COMMENT
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Unused Imports67 hits · 64 pts
SeverityFileLineSnippetContext
LOWdemo/multiclass_classification/train.py3CODE
LOWdemo/dask/dask_learning_to_rank.py16CODE
LOWdemo/nvflare/vertical/custom/trainer.py10CODE
LOWdemo/guide-python/cat_in_the_dat.py24CODE
LOWdemo/guide-python/learning_to_rank.py19CODE
LOWtests/test_distributed/test_with_spark/test_spark.py6CODE
LOWtests/test_distributed/test_gpu_with_dask/conftest.py21CODE
LOW…t_distributed/test_gpu_with_dask/test_gpu_with_dask.py15CODE
LOWtests/test_distributed/test_with_dask/conftest.py3CODE
LOWtests/test_distributed/test_with_dask/test_with_dask.py1978CODE
LOWtests/test_distributed/test_with_dask/test_with_dask.py2069CODE
LOWtests/python-sycl/test_sycl_with_sklearn.py3CODE
LOWtests/python-sycl/test_sycl_prediction.py1CODE
LOWtests/python-sycl/test_sycl_prediction.py7CODE
LOWtests/python-sycl/test_sycl_updaters.py1CODE
LOWtests/python-sycl/test_sycl_updaters.py2CODE
LOWtests/python-sycl/test_sycl_updaters.py3CODE
LOWtests/python-sycl/test_sycl_updaters.py5CODE
LOWtests/python-sycl/test_sycl_updaters.py7CODE
LOWpython-package/xgboost/objective.py28CODE
LOWpython-package/xgboost/compat.py39CODE
LOWpython-package/xgboost/compat.py40CODE
LOWpython-package/xgboost/compat.py41CODE
LOWpython-package/xgboost/compat.py81CODE
LOWpython-package/xgboost/_typing.py34CODE
LOWpython-package/xgboost/__init__.py6CODE
LOWpython-package/xgboost/__init__.py6CODE
LOWpython-package/xgboost/__init__.py6CODE
LOWpython-package/xgboost/__init__.py12CODE
LOWpython-package/xgboost/__init__.py12CODE
LOWpython-package/xgboost/__init__.py12CODE
LOWpython-package/xgboost/__init__.py12CODE
LOWpython-package/xgboost/__init__.py12CODE
LOWpython-package/xgboost/__init__.py12CODE
LOWpython-package/xgboost/__init__.py20CODE
LOWpython-package/xgboost/__init__.py21CODE
LOWpython-package/xgboost/__init__.py21CODE
LOWpython-package/xgboost/__init__.py24CODE
LOWpython-package/xgboost/__init__.py24CODE
LOWpython-package/xgboost/__init__.py24CODE
LOWpython-package/xgboost/__init__.py25CODE
LOWpython-package/xgboost/__init__.py25CODE
LOWpython-package/xgboost/__init__.py25CODE
LOWpython-package/xgboost/__init__.py26CODE
LOWpython-package/xgboost/__init__.py26CODE
LOWpython-package/xgboost/__init__.py26CODE
LOWpython-package/xgboost/__init__.py26CODE
LOWpython-package/xgboost/__init__.py26CODE
LOWpython-package/xgboost/__init__.py26CODE
LOWpython-package/xgboost/core.py5CODE
LOWpython-package/xgboost/training.py42CODE
LOWpython-package/xgboost/data.py82CODE
LOWpython-package/xgboost/data.py83CODE
LOWpython-package/xgboost/data.py85CODE
LOWpython-package/xgboost/data.py85CODE
LOWpython-package/xgboost/_data_utils.py41CODE
LOWpython-package/xgboost/testing/__init__.py53CODE
LOWpython-package/xgboost/testing/__init__.py53CODE
LOWpython-package/xgboost/spark/params.py3CODE
LOWpython-package/xgboost/spark/__init__.py8CODE
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Hallucination Indicators4 hits · 45 pts
SeverityFileLineSnippetContext
CRITICALR-package/tests/testthat/test_dmatrix.R674 expect_equal(xgb.get.DMatrix.num.non.missing(dm1), 10)CODE
CRITICALR-package/tests/testthat/test_dmatrix.R679 expect_equal(xgb.get.DMatrix.num.non.missing(dm2), 8)CODE
CRITICALpython-package/xgboost/data.py501 # pandas.core.internals.managers.SingleBlockManager.array_values()COMMENT
CRITICAL…rc/main/java/ml/dmlc/xgboost4j/java/flink/XGBoost.java170 return new XGBoostModel(ml.dmlc.xgboost4j.java.XGBoost.loadModel(opened));CODE
Deep Nesting42 hits · 40 pts
SeverityFileLineSnippetContext
LOWdemo/guide-python/model_parser.py146CODE
LOWtests/python/test_model_compatibility.py29CODE
LOWtests/python/test_model_compatibility.py76CODE
LOWtests/python/test_shap.py12CODE
LOWtests/python/test_shap.py82CODE
LOWtests/python/test_tracker.py222CODE
LOWtests/python/test_tracker.py256CODE
LOWtests/python/test_tracker.py227CODE
LOWtests/python/test_tracker.py268CODE
LOWtests/test_distributed/test_with_dask/test_with_dask.py1741CODE
LOWtests/python-sycl/test_sycl_updaters.py61CODE
LOWtests/python-sycl/test_sycl_training_continuation.py9CODE
LOWtests/python-sycl/test_sycl_training_continuation.py29CODE
LOWpython-package/xgboost/callback.py555CODE
LOWpython-package/xgboost/callback.py634CODE
LOWpython-package/xgboost/core.py2321CODE
LOWpython-package/xgboost/core.py3084CODE
LOWpython-package/xgboost/libpath.py19CODE
LOWpython-package/xgboost/sklearn.py1173CODE
LOWpython-package/xgboost/sklearn.py1403CODE
LOWpython-package/xgboost/sklearn.py1833CODE
LOWpython-package/xgboost/data.py370CODE
LOWpython-package/xgboost/data.py534CODE
LOWpython-package/xgboost/data.py1074CODE
LOWpython-package/xgboost/dask/__init__.py1032CODE
LOWpython-package/xgboost/dask/__init__.py1560CODE
LOWpython-package/xgboost/dask/__init__.py1975CODE
LOWpython-package/xgboost/testing/ordinal.py124CODE
LOWpython-package/xgboost/testing/ordinal.py137CODE
LOWpython-package/xgboost/testing/continuation.py14CODE
LOWpython-package/xgboost/testing/continuation.py38CODE
LOWpython-package/xgboost/testing/shared.py53CODE
LOWpython-package/xgboost/spark/core.py1362CODE
LOWpython-package/xgboost/spark/core.py1388CODE
LOWpython-package/xgboost/spark/data.py174CODE
LOWpython-package/xgboost/spark/data.py213CODE
LOWdoc/conf.py65CODE
LOWops/script/run_clang_tidy.py103CODE
LOWops/script/lint_cpp.py13CODE
LOWops/script/lint_cpp.py135CODE
LOWops/script/change_scala_version.py7CODE
LOWops/script/test_r_package.py230CODE
AI Structural Patterns41 hits · 38 pts
SeverityFileLineSnippetContext
LOWtests/python/test_parse_tree.py34CODE
LOWtests/python-sycl/test_sycl_simple_dask.py17CODE
LOWpython-package/xgboost/callback.py269CODE
LOWpython-package/xgboost/collective.py146CODE
LOWpython-package/xgboost/collective.py158CODE
LOWpython-package/xgboost/plotting.py21CODE
LOWpython-package/xgboost/plotting.py154CODE
LOWpython-package/xgboost/core.py662CODE
LOWpython-package/xgboost/core.py860CODE
LOWpython-package/xgboost/core.py909CODE
LOWpython-package/xgboost/core.py1102CODE
LOWpython-package/xgboost/core.py1480CODE
LOWpython-package/xgboost/core.py1965CODE
LOWpython-package/xgboost/core.py2406CODE
LOWpython-package/xgboost/core.py2999CODE
LOWpython-package/xgboost/sklearn.py809CODE
LOWpython-package/xgboost/sklearn.py1270CODE
LOWpython-package/xgboost/sklearn.py1721CODE
LOWpython-package/xgboost/sklearn.py1974CODE
LOWpython-package/xgboost/sklearn.py2059CODE
LOWpython-package/xgboost/sklearn.py2167CODE
LOWpython-package/xgboost/training.py53CODE
LOWpython-package/xgboost/training.py435CODE
LOWpython-package/xgboost/training.py253CODE
LOWpython-package/xgboost/data.py1229CODE
LOWpython-package/xgboost/dask/__init__.py256CODE
LOWpython-package/xgboost/dask/__init__.py581CODE
LOWpython-package/xgboost/dask/__init__.py831CODE
LOWpython-package/xgboost/dask/__init__.py1211CODE
LOWpython-package/xgboost/dask/__init__.py296CODE
LOWpython-package/xgboost/dask/__init__.py591CODE
LOWpython-package/xgboost/dask/__init__.py1660CODE
LOWpython-package/xgboost/dask/__init__.py1772CODE
LOWpython-package/xgboost/dask/__init__.py1975CODE
LOWpython-package/xgboost/dask/__init__.py2144CODE
LOWpython-package/xgboost/dask/__init__.py2206CODE
LOWpython-package/xgboost/dask/data.py206CODE
LOWpython-package/xgboost/testing/data.py859CODE
LOWpython-package/xgboost/spark/estimator.py195CODE
LOWpython-package/xgboost/spark/estimator.py372CODE
LOWpython-package/xgboost/spark/estimator.py561CODE
AI Slop Vocabulary11 hits · 24 pts
SeverityFileLineSnippetContext
LOWdemo/rmm_plugin/rmm_mgpu_with_dask.py44 # To use RMM pool allocator with a GPU Dask cluster, just add rmm_pool_size optionCOMMENT
MEDIUMdemo/guide-python/custom_softmax.py70 # suitable for demo. Also the one in native XGBoost core is more robust toCOMMENT
MEDIUMpython-package/xgboost/config.py58 # Show all messages, including ones pertaining to debuggingCOMMENT
LOWpython-package/xgboost/sklearn.py1851 # If output_margin is active, simply return the scoresSTRING
MEDIUMpython-package/xgboost/dask/__init__.py690# dask paradigm. But as a side effect, the `evals_result` in single-node APICOMMENT
MEDIUMpython-package/xgboost/testing/__init__.py662 """Reassign stdout temporarily in order to test printed statementsSTRING
MEDIUMpython-package/xgboost/spark/core.py935 # Spark-rapids is a project to leverage GPUs to accelerate spark SQL.COMMENT
LOWpython-package/xgboost/spark/core.py673 # For now, since we cannot call rdd.getNumPartitions(), we just returnCOMMENT
LOWpython-package/xgboost/spark/core.py1351 # User don't set gpu configurations, just use cpuCOMMENT
MEDIUM…main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoost.scala144 // that utilize GPUs alongside training tasks in order to avoid GPU out-of-memory errors.COMMENT
MEDIUMsrc/common/cuda_pinned_allocator.h73// This is actually a pinned memory allocator in disguise. We utilize HMM or ATS forCOMMENT
Modern Structural Boilerplate20 hits · 20 pts
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LOWpython-package/xgboost/callback.py36__all__ = [CODE
LOWpython-package/xgboost/interpret.py127__all__ = ["shap_values"]CODE
LOWpython-package/xgboost/config.py127def set_config(**new_config: Any) -> None:STRING
LOWpython-package/xgboost/__init__.py41__all__ = [CODE
LOWpython-package/xgboost/core.py933 def set_float_info(self, field: str, data: ArrayLike) -> None:CODE
LOWpython-package/xgboost/core.py948 def set_float_info_npy2d(self, field: str, data: ArrayLike) -> None:CODE
LOWpython-package/xgboost/core.py964 def set_uint_info(self, field: str, data: ArrayLike) -> None:CODE
LOWpython-package/xgboost/core.py995 def set_label(self, label: ArrayLike) -> None:CODE
LOWpython-package/xgboost/core.py1007 def set_weight(self, weight: ArrayLike) -> None:CODE
LOWpython-package/xgboost/core.py1027 def set_base_margin(self, margin: ArrayLike) -> None:CODE
LOWpython-package/xgboost/core.py1045 def set_group(self, group: ArrayLike) -> None:CODE
LOWpython-package/xgboost/core.py2045 def set_attr(self, **kwargs: Optional[Any]) -> None:CODE
LOWpython-package/xgboost/core.py2075 def _set_feature_info(self, features: Optional[FeatureInfo], field: str) -> None:CODE
LOWpython-package/xgboost/sklearn.py1265 def _set_evaluation_result(self, evals_result: EvalsLog) -> None:CODE
LOWpython-package/xgboost/dask/__init__.py138__all__ = [CODE
LOWpython-package/xgboost/spark/__init__.py17__all__ = [CODE
LOWpython-package/xgboost/spark/core.py358 def _set_predict_params_default(self) -> None:CODE
LOWpython-package/xgboost/spark/core.py300 def _set_xgb_params_default(self) -> None:CODE
LOWpython-package/xgboost/spark/core.py336 def _set_fit_params_default(self) -> None:CODE
LOWpython-package/xgboost/spark/estimator.py41 def set_param_attrs(attr_name: str, param: Param) -> None:CODE
Self-Referential Comments6 hits · 18 pts
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MEDIUMdemo/guide-python/cat_pipeline.py66 # Create an encoder based on training data.COMMENT
MEDIUMR-package/R/utils.R2# This file is for the low level reusable utility functionsCOMMENT
MEDIUMR-package/inst/make-r-def.R2# Create a definition file (.def) from a .dll file, using objdump. ThisCOMMENT
MEDIUMtests/python-gpu/test_gpu_prediction.py266 # Create a wide datasetCOMMENT
MEDIUMpython-package/xgboost/dask/data.py434 # Create the training DMatrixCOMMENT
MEDIUMpython-package/xgboost/testing/data.py180 # Create a dictionary-backed dataframe, enable this when the roundtrip isCOMMENT
Cross-File Repetition3 hits · 15 pts
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HIGHdemo/guide-python/quantile_data_iterator.py0utility function for obtaining current batch of data.STRING
HIGHtests/python-gpu/test_from_cudf.py0utility function for obtaining current batch of data.STRING
HIGHpython-package/xgboost/dask/data.py0utility function for obtaining current batch of data.STRING
Cross-Language Confusion2 hits · 12 pts
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HIGHtests/python/test_with_pandas.py487 assert df.equals(copy)CODE
HIGHpython-package/xgboost/testing/data.py200 # assert pd_catcodes.equals(pa_catcodes)COMMENT
Excessive Try-Catch Wrapping11 hits · 12 pts
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LOWdemo/guide-python/distributed_extmem_basic.py189 except Exception as e:CODE
LOWtests/python/test_with_shap.py9except Exception:CODE
LOWtests/python/test_openmp.py44 except Exception as e:CODE
LOWpython-package/xgboost/core.py380 except Exception as e: # pylint: disable=broad-exceptCODE
LOWpython-package/xgboost/data.py1326 except Exception: # pylint: disable=broad-exceptCODE
MEDIUMpython-package/xgboost/data.py1002def _lazy_load_cudf_is_cat() -> Callable[[Any], bool]:CODE
LOWpython-package/xgboost/dask/__init__.py673 except Exception: # pylint: disable=broad-exceptCODE
LOWpython-package/xgboost/testing/__init__.py187 except Exception: # pylint: disable=broad-exceptCODE
LOWpython-package/xgboost/testing/__init__.py757 except Exception as e: # pylint: disable=broad-exceptCODE
LOWpython-package/xgboost/spark/core.py1654 except Exception as e: # pylint: disable=W0703CODE
LOWops/script/change_version.py163 except Exception as e:STRING
AI Response Leakage1 hit · 8 pts
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HIGHR-package/R/xgb.DMatrix.R664#' # In this example, batches are obtained by subsetting the 'x' variable.COMMENT
Decorative Section Separators2 hits · 6 pts
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MEDIUMpython-package/CMakeLists.txt26# ---------------------------------------------------------------------------COMMENT
MEDIUMpython-package/CMakeLists.txt28# ---------------------------------------------------------------------------COMMENT
Redundant / Tautological Comments4 hits · 6 pts
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LOWR-package/tests/testthat/test_ranking.R25 # Check if the metric is monotone increasingCOMMENT
LOWR-package/tests/testthat/test_ranking.R53 # Check if the metric is monotone increasingCOMMENT
LOWR-package/tests/testthat/test_ranking.R63 all(diff(z) <= 0) # Check if z is monotone decreasingCODE
LOWjvm-packages/create_jni.py80 # Set GPU_ARCH_FLAG to override the CUDA architectures.COMMENT
Slop Phrases1 hit · 3 pts
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MEDIUMdemo/guide-python/sklearn_evals_result.py25# Or you can use: clf = xgb.XGBClassifier(**param_dist)COMMENT
Verbosity Indicators2 hits · 3 pts
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LOWR-package/R/xgb.train.R420#' The purpose of this function is to enable IDE autocompletions and to provide in-packageCOMMENT
LOWpython-package/xgboost/spark/core.py1255 # all the columns specified by features_cols, so we need to check ifCOMMENT
Example Usage Blocks2 hits · 3 pts
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LOWops/pipeline/build-cuda.sh5## Usage:COMMENT
LOWops/pipeline/test-python-wheel.sh4## Usage:COMMENT