bugbug/models/regressionrange.py [30:78]:
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            bug_features.IsCoverityIssue(),
            bug_features.HasCrashSignature(),
            bug_features.HasURL(),
            bug_features.HasW3CURL(),
            bug_features.HasGithubURL(),
            bug_features.Whiteboard(),
            bug_features.Patches(),
            bug_features.Landings(),
        ]

        cleanup_functions = [
            feature_cleanup.fileref(),
            feature_cleanup.url(),
            feature_cleanup.synonyms(),
        ]

        self.extraction_pipeline = Pipeline(
            [
                (
                    "bug_extractor",
                    bug_features.BugExtractor(feature_extractors, cleanup_functions),
                ),
            ]
        )

        self.clf = ImblearnPipeline(
            [
                (
                    "union",
                    ColumnTransformer(
                        [
                            ("data", DictVectorizer(), "data"),
                            ("title", self.text_vectorizer(), "title"),
                            ("comments", self.text_vectorizer(), "comments"),
                        ]
                    ),
                ),
                ("sampler", RandomUnderSampler(random_state=0)),
                (
                    "estimator",
                    xgboost.XGBClassifier(n_jobs=utils.get_physical_cpu_count()),
                ),
            ]
        )

    def get_labels(self):
        classes = {}

        for bug_data in bugzilla.get_bugs():
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bugbug/models/stepstoreproduce.py [30:78]:
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            bug_features.IsCoverityIssue(),
            bug_features.HasCrashSignature(),
            bug_features.HasURL(),
            bug_features.HasW3CURL(),
            bug_features.HasGithubURL(),
            bug_features.Whiteboard(),
            bug_features.Patches(),
            bug_features.Landings(),
        ]

        cleanup_functions = [
            feature_cleanup.fileref(),
            feature_cleanup.url(),
            feature_cleanup.synonyms(),
        ]

        self.extraction_pipeline = Pipeline(
            [
                (
                    "bug_extractor",
                    bug_features.BugExtractor(feature_extractors, cleanup_functions),
                ),
            ]
        )

        self.clf = ImblearnPipeline(
            [
                (
                    "union",
                    ColumnTransformer(
                        [
                            ("data", DictVectorizer(), "data"),
                            ("title", self.text_vectorizer(), "title"),
                            ("comments", self.text_vectorizer(), "comments"),
                        ]
                    ),
                ),
                ("sampler", RandomUnderSampler(random_state=0)),
                (
                    "estimator",
                    xgboost.XGBClassifier(n_jobs=utils.get_physical_cpu_count()),
                ),
            ]
        )

    def get_labels(self):
        classes = {}

        for bug_data in bugzilla.get_bugs():
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