🕷️ Crawler Inspector

URL Lookup

Direct Parameter Lookup

Raw Queries and Responses

1. Shard Calculation

Query:

Response:

Calculated Shard: 169 (from laksa114)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa169.int.ahrefs:8124/' \
  -H 'Content-Type: text/plain' \
  -H 'X-ClickHouse-Database: crawler3' \
  -H 'Authorization: Basic YXBpOg==' \
  -d 'SELECT getAhrefsURLFromUnparsed(src_unparsed) AS found_url, ifNull(toUnixTimestamp(download_stamp), 0) AS crawl_time, ifNull(toUnixTimestamp(props_url_first_seen), 0) AS first_indexed_time, download_http_code AS http_code, src_unparsed AS src_unparsed, src_root_hash AS src_root_hash, history_drop_reason AS history_drop_reason, meta_title AS meta_title, meta_descriptions AS meta_descriptions, attrs_boilerpipe_text AS attrs_boilerpipe_text, attrs_markdown AS attrs_markdown, attrs_readable_markdown AS attrs_readable_markdown, meta_canonical AS meta_canonical FROM crawler3.page_info_local FINAL PREWHERE (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://catboost.ai/docs/en/features/eval-metrics\')), getAhrefsUnparsedNoserviceFromURL(\'https://catboost.ai/docs/en/features/eval-metrics\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/catboost.ai\/docs\/en\/features\/eval-metrics","crawl_time":1776468970,"first_indexed_time":1732070880,"http_code":200,"src_unparsed":"ai,catboost!\/docs\/en\/features\/eval-metrics s443","src_root_hash":"17435841955170310369","history_drop_reason":null,"meta_title":"Calculate metrics | CatBoost","meta_descriptions":["A list of specified metrics can be calculated for the given dataset using the Python package. Python package CatBoost. Class purpose."],"attrs_boilerpipe_text":"A list of specified metrics can be calculated for the given dataset using the   Python package.\nPython package\nCatBoost\nClass purpose\nTraining and applying models.\nMethod\neval_metrics\nDescription\nCalculate the specified metrics for the specified dataset.\nCatBoostRegressor\nClass purpose\nTraining and applying models.\nMethod\neval_metrics\nCatBoostClassifier\nClass purpose\nTraining and applying models.\nMethod\neval_metrics","attrs_markdown":"[![Logo icon](https:\/\/yastatic.net\/s3\/locdoc\/daas-static\/catboost\/71b237a322eec6f2889af0dae2a9c549.svg)](https:\/\/catboost.ai\/ \"CatBoost\")\n\n- Installation\n  - [Overview](https:\/\/catboost.ai\/docs\/en\/features\/en\/concepts\/installation)\n  - Python package installation\n  - CatBoost for Apache Spark installation\n  - R package installation\n  - Command-line version binary\n  - Build from source\n- Key Features\n  - [Training](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/training)\n  - [Training on GPU](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/training-on-gpu)\n  - [Regular prediction](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/prediction)\n  - [Staged prediction](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/staged-prediction)\n  - [Cross-validation](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/cross-validation)\n  - [Feature importances](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/feature-importances-calculation)\n  - [User-defined metrics](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/custom-loss-functions)\n  - [Using the overfitting detector](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/overfitting-detector-desc)\n  - [Export a model to CoreML](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/export-model-to-core-ml)\n  - [Pre-trained data](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/proceed-training)\n  - [Calculate metrics](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/eval-metrics)\n  - [Categorical features](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/categorical-features)\n  - [Text features](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/text-features)\n  - [Embeddings features](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/embeddings-features)\n  - [Aggregated graph features](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/graph-aggregated-features)\n  - [Implemented metrics](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/loss-functions-desc)\n  - [Export a model to Python or C++](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/export-model-to-python)\n  - [Export a model to JSON](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/export-model-to-json)\n  - [Object importances](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/object-importances-calcution)\n- Training parameters\n- Python package\n- CatBoost for Apache Spark\n- R package\n- Command-line version\n- Applying models\n- Objectives and metrics\n- Model analysis\n- Data format description\n- [Parameter tuning](https:\/\/catboost.ai\/docs\/en\/features\/en\/concepts\/parameter-tuning)\n- [Speeding up the training](https:\/\/catboost.ai\/docs\/en\/features\/en\/concepts\/speed-up-training)\n- Data visualization\n- Algorithm details\n- [FAQ](https:\/\/catboost.ai\/docs\/en\/features\/en\/concepts\/faq)\n- Educational materials\n- [Development and contributions](https:\/\/catboost.ai\/docs\/en\/features\/en\/concepts\/development-and-contributions)\n- [Contacts](https:\/\/catboost.ai\/docs\/en\/features\/en\/concepts\/contacts)\n\nCalculate metrics\n\n## In this article:\n- [Python package](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/eval-metrics#python-package)\n- [CatBoost](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/eval-metrics#catboost)\n- [CatBoostRegressor](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/eval-metrics#catboostregressor)\n- [CatBoostClassifier](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/eval-metrics#catboostclassifier)\n\n1. Key Features\n2. Calculate metrics\n\n# Calculate metrics\n- [Python package](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/eval-metrics#python-package)\n  - [CatBoost](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/eval-metrics#catboost)\n  - [CatBoostRegressor](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/eval-metrics#catboostregressor)\n  - [CatBoostClassifier](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/eval-metrics#catboostclassifier)\n\nA list of specified metrics can be calculated for the given dataset using the Python package.\n\n## Python package\n### [CatBoost](https:\/\/catboost.ai\/docs\/en\/features\/en\/concepts\/python-reference_catboost)\n**Class purpose**\n\nTraining and applying models.\n\n**Method**\n\n[eval\\_metrics](https:\/\/catboost.ai\/docs\/en\/features\/en\/concepts\/python-reference_catboost_eval-metrics)\n\n**Description**\n\nCalculate the specified metrics for the specified dataset.\n\n### [CatBoostRegressor](https:\/\/catboost.ai\/docs\/en\/features\/en\/concepts\/python-reference_catboostregressor)\n**Class purpose**\n\nTraining and applying models.\n\n**Method**\n\n[eval\\_metrics](https:\/\/catboost.ai\/docs\/en\/features\/en\/concepts\/python-reference_catboostregressor_eval-metrics)\n\n### [CatBoostClassifier](https:\/\/catboost.ai\/docs\/en\/features\/en\/concepts\/python-reference_catboostclassifier)\n**Class purpose**\n\nTraining and applying models.\n\n**Method**\n\n[eval\\_metrics](https:\/\/catboost.ai\/docs\/en\/features\/en\/concepts\/python-reference_catboostclassifier_eval-metrics)\n\n### Was the article helpful?\nYes\n\nNo\n\nPrevious\n\n[Pre-trained data](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/proceed-training)\n\nNext\n\n[Categorical features](https:\/\/catboost.ai\/docs\/en\/features\/en\/features\/categorical-features)\n\n![](https:\/\/mc.yandex.ru\/watch\/60763294)","attrs_readable_markdown":"A list of specified metrics can be calculated for the given dataset using the Python package.\n\n## Python package\n### [CatBoost](https:\/\/catboost.ai\/docs\/en\/concepts\/python-reference_catboost)\n**Class purpose**\n\nTraining and applying models.\n\n**Method**\n\n[eval\\_metrics](https:\/\/catboost.ai\/docs\/en\/concepts\/python-reference_catboost_eval-metrics)\n\n**Description**\n\nCalculate the specified metrics for the specified dataset.\n\n### [CatBoostRegressor](https:\/\/catboost.ai\/docs\/en\/concepts\/python-reference_catboostregressor)\n**Class purpose**\n\nTraining and applying models.\n\n**Method**\n\n[eval\\_metrics](https:\/\/catboost.ai\/docs\/en\/concepts\/python-reference_catboostregressor_eval-metrics)\n\n### [CatBoostClassifier](https:\/\/catboost.ai\/docs\/en\/concepts\/python-reference_catboostclassifier)\n**Class purpose**\n\nTraining and applying models.\n\n**Method**\n\n[eval\\_metrics](https:\/\/catboost.ai\/docs\/en\/concepts\/python-reference_catboostclassifier_eval-metrics)","meta_canonical":null}

3. Robots.txt Check

Query:

Response:

4. Spam/Ban Check

Query:

Response:

5. Seen Status Check

ℹ️ Skipped - page is already crawled

📄

INDEXABLE

✅

CRAWLED

1 day ago

🤖

ROBOTS ALLOWED

Page Info Filters

Filter	Status	Condition	Details
HTTP status	PASS	`download_http_code = 200`	HTTP 200
Age cutoff	PASS	`download_stamp > now() - 6 MONTH`	0 months ago
History drop	PASS	`isNull(history_drop_reason)`	No drop reason
Spam/ban	PASS	`fh_dont_index != 1 AND ml_spam_score = 0`	ml_spam_score=0
Canonical	PASS	`meta_canonical IS NULL OR = '' OR = src_unparsed`	Not set

Page Details

Property	Value
URL	https://catboost.ai/docs/en/features/eval-metrics
Last Crawled	2026-04-17 23:36:10 (1 day ago)
First Indexed	2024-11-20 02:48:00 (1 year ago)
HTTP Status Code	200
Meta Title	Calculate metrics \| CatBoost
Meta Description	A list of specified metrics can be calculated for the given dataset using the Python package. Python package CatBoost. Class purpose.
Meta Canonical	null
Boilerpipe Text	A list of specified metrics can be calculated for the given dataset using the Python package. Python package CatBoost Class purpose Training and applying models. Method eval_metrics Description Calculate the specified metrics for the specified dataset. CatBoostRegressor Class purpose Training and applying models. Method eval_metrics CatBoostClassifier Class purpose Training and applying models. Method eval_metrics
Markdown	[![Logo icon](https://yastatic.net/s3/locdoc/daas-static/catboost/71b237a322eec6f2889af0dae2a9c549.svg)](https://catboost.ai/ "CatBoost") - Installation - [Overview](https://catboost.ai/docs/en/features/en/concepts/installation) - Python package installation - CatBoost for Apache Spark installation - R package installation - Command-line version binary - Build from source - Key Features - [Training](https://catboost.ai/docs/en/features/en/features/training) - [Training on GPU](https://catboost.ai/docs/en/features/en/features/training-on-gpu) - [Regular prediction](https://catboost.ai/docs/en/features/en/features/prediction) - [Staged prediction](https://catboost.ai/docs/en/features/en/features/staged-prediction) - [Cross-validation](https://catboost.ai/docs/en/features/en/features/cross-validation) - [Feature importances](https://catboost.ai/docs/en/features/en/features/feature-importances-calculation) - [User-defined metrics](https://catboost.ai/docs/en/features/en/features/custom-loss-functions) - [Using the overfitting detector](https://catboost.ai/docs/en/features/en/features/overfitting-detector-desc) - [Export a model to CoreML](https://catboost.ai/docs/en/features/en/features/export-model-to-core-ml) - [Pre-trained data](https://catboost.ai/docs/en/features/en/features/proceed-training) - [Calculate metrics](https://catboost.ai/docs/en/features/en/features/eval-metrics) - [Categorical features](https://catboost.ai/docs/en/features/en/features/categorical-features) - [Text features](https://catboost.ai/docs/en/features/en/features/text-features) - [Embeddings features](https://catboost.ai/docs/en/features/en/features/embeddings-features) - [Aggregated graph features](https://catboost.ai/docs/en/features/en/features/graph-aggregated-features) - [Implemented metrics](https://catboost.ai/docs/en/features/en/features/loss-functions-desc) - [Export a model to Python or C++](https://catboost.ai/docs/en/features/en/features/export-model-to-python) - [Export a model to JSON](https://catboost.ai/docs/en/features/en/features/export-model-to-json) - [Object importances](https://catboost.ai/docs/en/features/en/features/object-importances-calcution) - Training parameters - Python package - CatBoost for Apache Spark - R package - Command-line version - Applying models - Objectives and metrics - Model analysis - Data format description - [Parameter tuning](https://catboost.ai/docs/en/features/en/concepts/parameter-tuning) - [Speeding up the training](https://catboost.ai/docs/en/features/en/concepts/speed-up-training) - Data visualization - Algorithm details - [FAQ](https://catboost.ai/docs/en/features/en/concepts/faq) - Educational materials - [Development and contributions](https://catboost.ai/docs/en/features/en/concepts/development-and-contributions) - [Contacts](https://catboost.ai/docs/en/features/en/concepts/contacts) Calculate metrics ## In this article: - [Python package](https://catboost.ai/docs/en/features/en/features/eval-metrics#python-package) - [CatBoost](https://catboost.ai/docs/en/features/en/features/eval-metrics#catboost) - [CatBoostRegressor](https://catboost.ai/docs/en/features/en/features/eval-metrics#catboostregressor) - [CatBoostClassifier](https://catboost.ai/docs/en/features/en/features/eval-metrics#catboostclassifier) 1. Key Features 2. Calculate metrics # Calculate metrics - [Python package](https://catboost.ai/docs/en/features/en/features/eval-metrics#python-package) - [CatBoost](https://catboost.ai/docs/en/features/en/features/eval-metrics#catboost) - [CatBoostRegressor](https://catboost.ai/docs/en/features/en/features/eval-metrics#catboostregressor) - [CatBoostClassifier](https://catboost.ai/docs/en/features/en/features/eval-metrics#catboostclassifier) A list of specified metrics can be calculated for the given dataset using the Python package. ## Python package ### [CatBoost](https://catboost.ai/docs/en/features/en/concepts/python-reference_catboost) Class purpose Training and applying models. Method [eval\_metrics](https://catboost.ai/docs/en/features/en/concepts/python-reference_catboost_eval-metrics) Description Calculate the specified metrics for the specified dataset. ### [CatBoostRegressor](https://catboost.ai/docs/en/features/en/concepts/python-reference_catboostregressor) Class purpose Training and applying models. Method [eval\_metrics](https://catboost.ai/docs/en/features/en/concepts/python-reference_catboostregressor_eval-metrics) ### [CatBoostClassifier](https://catboost.ai/docs/en/features/en/concepts/python-reference_catboostclassifier) Class purpose Training and applying models. Method [eval\_metrics](https://catboost.ai/docs/en/features/en/concepts/python-reference_catboostclassifier_eval-metrics) ### Was the article helpful? Yes No Previous [Pre-trained data](https://catboost.ai/docs/en/features/en/features/proceed-training) Next [Categorical features](https://catboost.ai/docs/en/features/en/features/categorical-features) ![](https://mc.yandex.ru/watch/60763294)
Readable Markdown	A list of specified metrics can be calculated for the given dataset using the Python package. ## Python package ### [CatBoost](https://catboost.ai/docs/en/concepts/python-reference_catboost) Class purpose Training and applying models. Method [eval\_metrics](https://catboost.ai/docs/en/concepts/python-reference_catboost_eval-metrics) Description Calculate the specified metrics for the specified dataset. ### [CatBoostRegressor](https://catboost.ai/docs/en/concepts/python-reference_catboostregressor) Class purpose Training and applying models. Method [eval\_metrics](https://catboost.ai/docs/en/concepts/python-reference_catboostregressor_eval-metrics) ### [CatBoostClassifier](https://catboost.ai/docs/en/concepts/python-reference_catboostclassifier) Class purpose Training and applying models. Method [eval\_metrics](https://catboost.ai/docs/en/concepts/python-reference_catboostclassifier_eval-metrics)
Shard	169 (laksa)
Root Hash	17435841955170310369
Unparsed URL	ai,catboost!/docs/en/features/eval-metrics s443