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

6.5 Low AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of dmlc/xgboost, a C++ project with 28,705 GitHub stars. SynthScan v2.0 examined 143,174 lines of code across 743 source files, recording 832 pattern matches distributed across 18 syntactic categories. The overall adjusted score of 6.5 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).

6.5
Adjusted Score
6.5
Raw Score
100%
Time Factor
2026-08-27
Last Push
28.7K
Stars
C++
Language
143.2K
Lines of Code
743
Files
832
Pattern Hits
2026-08-29
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 16LOW 806

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 832 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 Identifiers298 hits · 319 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/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.py33def test_cat_container_model_slice() -> None:CODE
LOWtests/python/test_ordinal.py56def test_pd_cat_nullable_integer(CODE
LOWtests/python/test_ordinal.py77def test_pd_cat_nullable_float() -> None:CODE
LOWtests/python/test_ordinal.py130def test_training_continuation() -> None:CODE
LOWtests/python/test_ordinal.py138def 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.py198 def test_dmatrix_numpy_init_omp(self):CODE
LOWtests/python/test_basic.py234 def test_cv_explicit_fold_indices(self):CODE
LOWtests/python/test_basic.py248 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.py38 def test_arrow_table_with_custom_feature_names(self, DMatrixT):CODE
LOWtests/python/test_with_arrow.py47 def test_arrow_table_with_label(self):CODE
LOWtests/python/test_plotting.py104 def test_importance_plot_show_values(self) -> None: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/test_tree_regularization.py69 def test_absolute_error_lambda(self):CODE
LOWtests/python/test_tree_regularization.py93 def test_quantile_error_lambda(self):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.py238 def test_feature_names_validation(self):CODE
LOWtests/python/test_basic_models.py254 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.py65 def test_dmatrix_numpy_non_native_byte_order(self):CODE
LOWtests/python/test_predict.py76def 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.py52def test_shap_multi_output_tree() -> None:CODE
LOWtests/python/test_multi_target.py203def test_feature_importance_strategy_compare() -> None:CODE
LOWtests/python/test_multi_target.py217def test_gradient_based_sampling_accuracy() -> None:CODE
LOWtests/python/test_multi_target.py221def test_dart_normalization_multi_output_eta() -> 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
238 more matches not shown…
Over-Commented Block322 hits · 302 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:tweedie"`: Tweedie regression with log-link. It might be useful, e.g., for modeling total loss in insurance, COMMENT
LOWR-package/R/xgboost.R961#' @param monitor_training Whether to monitor objective optimization progress on the input data.COMMENT
LOWR-package/R/xgboost.R981#' if there is no improvement in performance (as measured by the last metric passed underCOMMENT
LOWR-package/R/xgboost.R1001#' a monotonically increasing function of that feature (that is, as the value of the featureCOMMENT
LOWR-package/R/xgboost.R1021#' @param feature_weights Feature weights for column sampling.COMMENT
LOWR-package/R/xgboost.R1041#' the corresponding `y` - `base_margin` should have the same column order that the model will useCOMMENT
LOWR-package/R/xgboost.R1061#' - L2 regularization term on weights. Increasing this value will make model more conservative. Normalised to number COMMENT
LOWR-package/R/xgboost.R1081#' data(mtcars)COMMENT
LOWR-package/R/xgboost.R1101#' # Can calculate evaluation metrics during boosting roundsCOMMENT
LOWR-package/R/xgboost.R1241#' @title Compute predictions from XGBoost model on new dataCOMMENT
LOWR-package/R/xgboost.R1261#' matched by name by default (see `validate_features`).COMMENT
LOWR-package/R/xgboost.R1281#' untransformed margin (e.g., for binary classification, the values are log-odds deviations fromCOMMENT
LOWR-package/R/xgboost.R1301#' (for objectives which produces a single score per observation), or a matrix with number ofCOMMENT
LOWR-package/R/xgboost.R1321#' and come in the same order as in the training data.COMMENT
LOWR-package/R/xgboost.R1541 "\n",COMMENT
LOWR-package/R/xgboost.R1561#'COMMENT
LOWR-package/R/xgboost.R1581#' - `data`: A sparse Matrix of 'dgCMatrix' class with 126 columns.COMMENT
LOWR-package/R/xgboost.R1601#' @importFrom data.table data.tableCOMMENT
262 more matches not shown…
Unused Imports70 hits · 66 pts
SeverityFileLineSnippetContext
LOWdemo/multiclass_classification/train.py3CODE
LOWdemo/dask/dask_learning_to_rank.py16CODE
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.py20CODE
LOWtests/test_distributed/test_with_dask/conftest.py3CODE
LOWtests/test_distributed/test_with_dask/test_with_dask.py2034CODE
LOWtests/test_distributed/test_with_dask/test_with_dask.py2125CODE
LOWtests/python-gpu/test_gpu_multi_target.py4CODE
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.py4CODE
LOWpython-package/xgboost/compat.py41CODE
LOWpython-package/xgboost/compat.py42CODE
LOWpython-package/xgboost/compat.py43CODE
LOWpython-package/xgboost/compat.py83CODE
LOWpython-package/xgboost/_typing.py33CODE
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.py84CODE
LOWpython-package/xgboost/data.py86CODE
LOWpython-package/xgboost/data.py86CODE
LOWpython-package/xgboost/_data_utils.py41CODE
LOWpython-package/xgboost/dask/utils.py8CODE
LOWpython-package/xgboost/testing/__init__.py52CODE
LOWpython-package/xgboost/testing/__init__.py52CODE
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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.py496 # 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 Nesting40 hits · 38 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.py1796CODE
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.py2356CODE
LOWpython-package/xgboost/core.py3119CODE
LOWpython-package/xgboost/libpath.py19CODE
LOWpython-package/xgboost/sklearn.py1237CODE
LOWpython-package/xgboost/sklearn.py1433CODE
LOWpython-package/xgboost/sklearn.py1849CODE
LOWpython-package/xgboost/data.py365CODE
LOWpython-package/xgboost/data.py529CODE
LOWpython-package/xgboost/data.py1046CODE
LOWpython-package/xgboost/dask/__init__.py1008CODE
LOWpython-package/xgboost/dask/__init__.py1536CODE
LOWpython-package/xgboost/dask/__init__.py1966CODE
LOWpython-package/xgboost/testing/ordinal.py124CODE
LOWpython-package/xgboost/testing/ordinal.py135CODE
LOWpython-package/xgboost/testing/continuation.py17CODE
LOWpython-package/xgboost/testing/continuation.py41CODE
LOWpython-package/xgboost/testing/shared.py55CODE
LOWpython-package/xgboost/spark/core.py1362CODE
LOWpython-package/xgboost/spark/core.py1388CODE
LOWpython-package/xgboost/spark/data.py189CODE
LOWpython-package/xgboost/spark/data.py228CODE
LOWdoc/conf.py65CODE
LOWops/script/lint_cpp.py13CODE
LOWops/script/lint_cpp.py135CODE
LOWops/script/change_scala_version.py7CODE
AI Structural Patterns33 hits · 30 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.py135CODE
LOWpython-package/xgboost/collective.py147CODE
LOWpython-package/xgboost/plotting.py21CODE
LOWpython-package/xgboost/plotting.py154CODE
LOWpython-package/xgboost/core.py676CODE
LOWpython-package/xgboost/core.py882CODE
LOWpython-package/xgboost/core.py931CODE
LOWpython-package/xgboost/core.py1124CODE
LOWpython-package/xgboost/core.py1496CODE
LOWpython-package/xgboost/core.py2007CODE
LOWpython-package/xgboost/core.py2441CODE
LOWpython-package/xgboost/core.py3034CODE
LOWpython-package/xgboost/sklearn.py871CODE
LOWpython-package/xgboost/sklearn.py2186CODE
LOWpython-package/xgboost/training.py53CODE
LOWpython-package/xgboost/training.py435CODE
LOWpython-package/xgboost/training.py253CODE
LOWpython-package/xgboost/data.py1201CODE
LOWpython-package/xgboost/dask/__init__.py245CODE
LOWpython-package/xgboost/dask/__init__.py570CODE
LOWpython-package/xgboost/dask/__init__.py810CODE
LOWpython-package/xgboost/dask/__init__.py1187CODE
LOWpython-package/xgboost/dask/__init__.py285CODE
LOWpython-package/xgboost/dask/__init__.py580CODE
LOWpython-package/xgboost/dask/__init__.py1966CODE
LOWpython-package/xgboost/dask/data.py206CODE
LOWpython-package/xgboost/testing/data.py882CODE
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.py1867 # If output_margin is active, simply return the scoresSTRING
MEDIUMpython-package/xgboost/dask/__init__.py672# dask paradigm. But as a side effect, the `evals_result` in single-node APICOMMENT
MEDIUMpython-package/xgboost/testing/__init__.py638 """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 Boilerplate21 hits · 21 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.py955 def set_float_info(self, field: str, data: ArrayLike) -> None:CODE
LOWpython-package/xgboost/core.py970 def set_float_info_npy2d(self, field: str, data: ArrayLike) -> None:CODE
LOWpython-package/xgboost/core.py986 def set_uint_info(self, field: str, data: ArrayLike) -> None:CODE
LOWpython-package/xgboost/core.py1017 def set_label(self, label: ArrayLike) -> None:CODE
LOWpython-package/xgboost/core.py1029 def set_weight(self, weight: ArrayLike) -> None:CODE
LOWpython-package/xgboost/core.py1049 def set_base_margin(self, margin: ArrayLike) -> None:CODE
LOWpython-package/xgboost/core.py1067 def set_group(self, group: ArrayLike) -> None:CODE
LOWpython-package/xgboost/core.py1835 def _set_params(self, params: List[Tuple[str, str]]) -> None:CODE
LOWpython-package/xgboost/core.py2087 def set_attr(self, **kwargs: Optional[Any]) -> None:CODE
LOWpython-package/xgboost/core.py2117 def _set_feature_info(self, features: Optional[FeatureInfo], field: str) -> None:CODE
LOWpython-package/xgboost/sklearn.py1304 def _set_evaluation_result(self, evals_result: EvalsLog) -> None:CODE
LOWpython-package/xgboost/dask/__init__.py127__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 Comments5 hits · 15 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
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.py399 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.py187 except Exception as e:CODE
LOWtests/python/test_with_shap.py9except Exception:CODE
LOWtests/python/test_openmp.py47 except Exception as e:CODE
LOWpython-package/xgboost/core.py394 except Exception as e: # pylint: disable=broad-exceptCODE
LOWpython-package/xgboost/data.py1293 except Exception: # pylint: disable=broad-exceptCODE
MEDIUMpython-package/xgboost/data.py974def _lazy_load_cudf_is_cat() -> Callable[[Any], bool]:CODE
LOWpython-package/xgboost/dask/__init__.py659 except Exception: # pylint: disable=broad-exceptCODE
LOWpython-package/xgboost/testing/__init__.py186 except Exception: # pylint: disable=broad-exceptCODE
LOWpython-package/xgboost/testing/__init__.py733 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.py146 except Exception as e:STRING
AI Response Leakage1 hit · 8 pts
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HIGHR-package/R/xgb.DMatrix.R666#' # 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.txt21# ---------------------------------------------------------------------------COMMENT
MEDIUMpython-package/CMakeLists.txt23# ---------------------------------------------------------------------------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