{"id":"1f695fc0-fbc4-41fb-94c4-1f16e9135136","entity_type":"product","name":"CatBoost","slug":"catboost","category":"ML Framework","description":{"human":"Yandex's gradient boosting library. Handles categorical features natively without preprocessing."},"url":"https://catboost.ai","metadata":{"content":"Yandex's gradient boosting library. Handles categorical features natively without preprocessing.","crawled_problems":{"total":9,"by_source":{"github":9,"reddit":0,"stackoverflow":0},"crawled_at":"2026-03-27T04:43:06.871757+00:00","top_issues":[{"url":"https://github.com/catboost/catboost/issues/3059","state":"open","title":"CUDA 12.8 - A6000/A100/H100 - Integrity checks failed","labels":["need info","GPU","Linux"],"source":"github","comments":6,"reactions":1,"created_at":"2026-03-14T18:29:08Z","body_preview":"Attempting to use `CatBoost` on CUDA 12.8 architecture causes an `integrity checks failed`.  \nTorch recognises the CUDA installation, and available GPUs.  \nError occurs both when attempting `model.fit(...) `with GPU, and when running `get_gpu_device_count`\n\n`ubuntu@thunder-client:~# python gpu_test."},{"url":"https://github.com/catboost/catboost/issues/3038","state":"open","title":"The kernel appears to have died. It will restart automatically, when task_type='GPU' and loss_function = 'MultiLogloss","labels":["need info","GPU","python","crash"],"source":"github","comments":4,"reactions":0,"created_at":"2026-02-20T12:17:08Z","body_preview":"Problem: Got this error message on Jupyter Notebook when using GPU.\nCatBoost version: 1.2.7\nGPU: NVIDIA A100 80GB PCIe\nPython: 3.10.11\n```\nfrom catboost import CatBoostClassifier, Pool\nfrom catboost.utils import eval_metric\n\ntrain_pool = Pool(X_train, y_train)\nval_pool = Pool(X_val, y_val)\n\ncb = Cat"},{"url":"https://github.com/catboost/catboost/issues/3042","state":"open","title":"Build failure for `catboost==1.2.10` due to unsatisfiable `jupyterlab` / `notebook` / `ipykernel` dependency constraints (Python 3.12)","labels":["need info","build","python","installation"],"source":"github","comments":3,"reactions":0,"created_at":"2026-02-24T16:44:20Z","body_preview":"---\n\n### Description\n\nBuilding `catboost==1.2.10` fails during installation of build-backend dependencies due to an unsatisfiable dependency chain involving `jupyterlab`, `notebook`, `ipykernel`, and `jupyter-client`.\n\nThe resolver reports that:\n\n* `ipykernel==7.2.0` depends on `jupyter-client>=8.8."},{"url":"https://github.com/catboost/catboost/issues/3064","state":"open","title":"`cat_features` rejected when input is a float numpy array, limits integration with ML frameworks","labels":["python"],"source":"github","comments":0,"reactions":1,"created_at":"2026-03-17T12:58:47Z","body_preview":"Hi CatBoost team,\n\nI'm Javier, one of the core developers of [skforecast](https://github.com/skforecast/skforecast), a Python library for time series forecasting with machine learning. We rely on CatBoost as one of our recommended estimators, and we've recently run into a limitation that we'd like t"},{"url":"https://github.com/catboost/catboost/issues/3020","state":"open","title":"Default loss function is not detected in case of multi-dimensional label","labels":["python","objectives and metrics"],"source":"github","comments":1,"reactions":0,"created_at":"2026-02-04T21:39:41Z","body_preview":"An error with a cryptic message is reported instead:\n\n```\n    is_multiclass_task = len(set(label)) > 2 and 'target_border' not in params\nE   TypeError: unhashable type: 'numpy.ndarray'\n```"}]}},"trust_signals":{},"tags":[],"trust_up":1,"trust_down":0,"trust_score":1,"trust_ratio":1,"velocity_7d":0,"evaluation_count":1,"verification_status":"unverified","verification_badges":[],"verified_at":null,"claim_status":"unclaimed","views":246,"version":1,"previous_version_id":null,"tier":"free","logo_url":null,"created_at":"2026-03-27T04:39:34.376209+00:00","updated_at":"2026-09-16T07:49:29.352905+00:00","review_summary":{},"community_up":3,"community_down":3,"community_score":0,"problem_count":0,"resolved_count":0,"confidence_decomposition":{"api_stability":null,"documentation_quality":null,"integration_success_rate":null,"cost_efficiency":null,"security_posture":null,"axes":null,"status":"no_operational_reports","sample_size":0,"current_reports":0,"required_reports":3,"computed_axes":[],"missing_axes":["api_stability","documentation_quality","integration_success_rate","cost_efficiency","security_posture"],"evidence_state":"no_operational_reports","task_type":"*","window":"all","message":"No agent has submitted an execution report for this entity yet. 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