feat(skore/checks): Add baseline comparison checks (SKD009, SKD010)

[GaetandeCast]

Change description

Adds two new automated checks to EstimatorReport.checks.summarize (and via aggregation to CrossValidationReport / ComparisonReport):

• SKD009 — Model worse than baseline: flags when test scores are not significantly better than a skrub.tabular_pipeline wrapped HistGradientBoostingClassifier / HistGradientBoostingRegressor baseline (same train/test data, same metric set). Vote per non-timing metric, strict majority triggers the issue.
• SKD010 — Model slower than baseline: flags when fit_time_ is at least 2x the fit time of a skrub.tabular_pipeline wrapped fast linear baseline (LogisticRegression for classification, RidgeCV for regression), AND the strict-majority "not significantly better than baseline" vote holds on test metrics. A 0.05s absolute floor on the time gap avoids noise on very fast fits.

Both checks raise CheckNotApplicable for unsupported ml tasks (multioutput, clustering, unknown) and when train+test data is unavailable. They share a single _baseline_estimator_report(report, kind=...) factory with kinds "dummy" / "performance" / "fast" — also used by the existing SKD002 underfitting check.

Companion refactor of SKD001 / SKD002 / SKD003 to read MetricsSummaryDisplay.rows directly (the MetricsSummaryRow TypedDict) instead of parsing the summary DataFrame. Metrics are now aligned by an identity tuple (verbose_name, label, average, output) rather than relying on row-order between two summarize() calls, which also lets _TIMING_METRICS shrink to the two canonical Metric.verbose_name values.

Closes #2668.

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• A new changelog entry was added to CHANGELOG.rst (if necessary; typically, if your change requires updating tests)
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AI usage disclosure

AI tools were involved for:

• Code generation (e.g., when writing an implementation or fixing a bug)
• Test/benchmark generation
• Documentation (including examples)
• Research and understanding

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Documentation preview @ d051986

[github-actions]

Coverage Report for skore/

File	Stmts	Miss	Branch	BrPart	Cover	Missing
skore/src/skore
__init__.py	39	2	2	0	94%	112–113
_config.py	58	3	12	1	94%	71, 118–119
exceptions.py	4	4	0	0	0%	4, 15, 19, 23
skore/src/skore/_plugins
__init__.py	12	0	0	0	100%
skore/src/skore/_plugins/hub
__init__.py	9	2	0	0	77%	15, 20
exception.py	2	0	0	0	100%
json.py	10	1	2	1	90%	16
skore/src/skore/_plugins/hub/artifact
__init__.py	0	0	0	0	100%
artifact.py	23	0	4	0	100%
serializer.py	27	0	2	0	100%
upload.py	26	0	4	0	100%
skore/src/skore/_plugins/hub/artifact/media
__init__.py	5	0	0	0	100%
data.py	20	0	0	0	100%
inspection.py	72	10	20	8	86%	46–49, 51, 53, 60, 62, 68, 107
media.py	10	0	0	0	100%
model.py	10	0	0	0	100%
performance.py	106	1	8	1	99%	43
skore/src/skore/_plugins/hub/artifact/pickle
__init__.py	2	0	0	0	100%
pickle.py	24	0	2	0	100%
skore/src/skore/_plugins/hub/authentication
__init__.py	0	0	0	0	100%
apikey.py	7	0	0	0	100%
login.py	28	4	4	2	85%	37, 42–43, 52
token.py	80	0	8	0	100%
uri.py	6	0	0	0	100%
skore/src/skore/_plugins/hub/client
__init__.py	0	0	0	0	100%
client.py	88	10	18	3	88%	140, 187–189, 191–192, 194, 196, 198, 230
skore/src/skore/_plugins/hub/metric
__init__.py	10	0	0	0	100%
accuracy.py	35	0	0	0	100%
brier_score.py	35	0	0	0	100%
log_loss.py	35	0	0	0	100%
metric.py	55	4	2	1	92%	38, 77–78, 84
precision.py	57	0	0	0	100%
r2.py	35	0	0	0	100%
recall.py	59	0	0	0	100%
rmse.py	35	0	0	0	100%
roc_auc.py	35	0	0	0	100%
timing.py	76	4	0	0	94%	45–46, 104–105
skore/src/skore/_plugins/hub/project
__init__.py	0	0	0	0	100%
project.py	138	6	26	5	95%	84, 109, 124, 323, 403, 433
skore/src/skore/_plugins/hub/report
__init__.py	3	0	0	0	100%
cross_validation_report.py	121	2	28	3	98%	224, 264
estimator_report.py	10	0	0	0	100%
report.py	60	0	6	0	100%
skore/src/skore/_plugins/local
__init__.py	2	0	0	0	100%
metadata.py	81	3	8	1	96%	29, 141–142
project.py	93	1	30	1	98%	238
storage.py	42	2	6	1	95%	45, 189
skore/src/skore/_plugins/mlflow
__init__.py	5	0	0	0	100%
project.py	209	15	54	5	92%	202, 233–234, 380, 382, 398, 400–405, 407–409
reports.py	155	6	34	4	96%	129, 170, 207–208, 270, 283
skore/src/skore/_project
__init__.py	0	0	0	0	100%
_summary.py	80	1	38	3	98%	121
_widget.py	191	0	44	2	100%
dependencies.py	19	0	6	0	100%
git.py	25	0	4	0	100%
login.py	17	3	6	2	82%	62, 71–72
plugin.py	12	0	2	0	100%
project.py	56	2	16	3	96%	132, 141
types.py	3	0	0	0	100%
skore/src/skore/_sklearn
__init__.py	8	0	0	0	100%
_base.py	54	1	10	0	98%	44
compare.py	5	0	0	0	100%
evaluate.py	43	0	24	0	100%
feature_names.py	26	0	12	0	100%
find_ml_task.py	61	0	46	2	100%
metrics.py	330	0	74	0	100%
types.py	19	1	0	0	94%	31
skore/src/skore/_sklearn/_checks
__init__.py	3	0	0	0	100%
_utils.py	58	3	20	3	94%	75, 175, 183
accessor.py	33	1	14	0	96%	17
base.py	76	5	24	3	93%	128–129, 169, 257–258
model_checks.py	221	5	56	5	97%	359, 367, 403, 407, 516
skore/src/skore/_sklearn/_comparison
__init__.py	9	0	0	0	100%
inspection_accessor.py	27	1	2	0	96%	347
metrics_accessor.py	125	4	18	4	96%	259–260, 329, 1164
report.py	160	5	68	0	96%	577, 583, 641–643
skore/src/skore/_sklearn/_cross_validation
__init__.py	11	0	0	0	100%
data_accessor.py	36	2	12	2	94%	48, 74
inspection_accessor.py	27	1	2	0	96%	319
metrics_accessor.py	123	3	18	3	97%	214–215, 1129
report.py	202	10	48	6	95%	73, 78, 83, 324, 598, 642, 648, 734–736
skore/src/skore/_sklearn/_estimator
__init__.py	11	0	0	0	100%
data_accessor.py	48	2	20	1	95%	61, 178
inspection_accessor.py	37	1	8	2	97%	278
metrics_accessor.py	127	0	22	0	100%
report.py	329	14	92	10	95%	60, 74, 295, 368, 453, 710, 799, 818, 820, 826–827, 914–916
skore/src/skore/_sklearn/_plot
__init__.py	3	0	0	0	100%
base.py	61	2	14	1	96%	61–62
utils.py	145	3	66	3	97%	254–255, 428
skore/src/skore/_sklearn/_plot/data
__init__.py	2	0	0	0	100%
table_report.py	177	1	60	1	99%	670
skore/src/skore/_sklearn/_plot/inspection
__init__.py	0	0	0	0	100%
coefficients.py	181	0	88	1	100%
impurity_decrease.py	103	2	34	3	98%	423, 467
permutation_importance.py	198	1	90	1	99%	585
utils.py	32	0	10	0	100%
skore/src/skore/_sklearn/_plot/metrics
__init__.py	6	0	0	0	100%
confusion_matrix.py	198	0	66	2	100%
metrics_summary_display.py	152	1	74	2	99%	290
precision_recall_curve.py	113	0	32	1	100%
prediction_error.py	166	0	54	2	100%
roc_curve.py	119	0	34	2	100%
skore/src/skore/_sklearn/train_test_split
__init__.py	2	0	0	0	100%
train_test_split.py	71	0	34	2	100%
skore/src/skore/_sklearn/train_test_split/warning
__init__.py	8	0	0	0	100%
high_class_imbalance_too_few_examples_warning.py	19	1	6	1	94%	83
high_class_imbalance_warning.py	20	0	6	0	100%
random_state_unset_warning.py	10	0	2	0	100%
shuffle_true_warning.py	9	0	2	0	100%
stratify_is_set_warning.py	10	0	2	0	100%
time_based_column_warning.py	21	0	4	0	100%
train_test_split_warning.py	3	0	0	0	100%
skore/src/skore/_utils
__init__.py	6	2	0	0	66%	8, 13
_accessor.py	106	28	30	13	73%	12–13, 15, 36, 61–65, 68, 70–71, 76, 81, 83, 85, 92–94, 120–121, 123–124, 126, 132, 164, 218, 238
_cache.py	37	0	2	1	100%
_cache_key.py	35	5	22	5	85%	22, 24, 51, 59, 68
_callable_name.py	9	0	4	0	100%
_dataframe.py	43	4	18	4	90%	27, 46, 48, 63
_environment.py	33	2	10	3	93%	46, 49
_fixes.py	8	0	2	0	100%
_index.py	5	0	2	0	100%
_jupyter.py	8	2	0	0	75%	13–14
_measure_time.py	10	0	0	0	100%
_parallel.py	17	0	0	0	100%
_patch.py	21	12	8	8	42%	30, 35–39, 42–43, 46–47, 58, 60
_progress_bar.py	42	4	4	0	90%	53–54, 64–65
_show_versions.py	38	0	12	0	100%
_skrub.py	37	0	4	0	100%
_testing.py	128	14	12	2	89%	24, 33, 71–72, 94, 193, 202, 213–218, 220
skore/src/skore/_utils/repr
__init__.py	2	0	0	0	100%
base.py	54	0	4	0	100%
data.py	128	0	30	1	100%
html_repr.py	40	0	0	0	100%
rich_repr.py	80	0	22	3	100%
utils.py	11	0	2	0	100%
TOTAL	7393	229	1852	150	96%

Tests	Skipped	Failures	Errors	Time
2585	6 💤	0 ❌	0 🔥	8m 56s ⏱️

[auguste-probabl]

Some nitpicks but this is pretty much good to go!