🕷️ Crawler Inspector

[](https://catboost.ai/ "CatBoost") - Installation - [Overview](https://catboost.ai/docs/en/concepts/en/concepts/installation) - Python package installation - CatBoost for Apache Spark installation - R package installation - Command-line version binary - Build from source - Key Features - Training parameters - Python package - CatBoost for Apache Spark - R package - Command-line version - [Train a model](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_train-model) - [Cross-validation](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_cross-validation) - [Scale and bias](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_normalize-model) - [Apply a model](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_calc-model) - [Calculate metrics](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics) - [Calculate feature importance](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_fstr-calc) - [Calculate object importance](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_ostr-calc) - [Metadata manipulation](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_metadata-manipulation) - [Select features](https://catboost.ai/docs/en/concepts/en/concepts/cli-select-features) - [Sum models](https://catboost.ai/docs/en/concepts/en/concepts/cli-sum-models) - [Distributed learning](https://catboost.ai/docs/en/concepts/en/concepts/cli-distributed-learning) - [Usage examples](https://catboost.ai/docs/en/concepts/en/concepts/cli-usages-examples) - Applying models - Objectives and metrics - Model analysis - Data format description - [Parameter tuning](https://catboost.ai/docs/en/concepts/en/concepts/parameter-tuning) - [Speeding up the training](https://catboost.ai/docs/en/concepts/en/concepts/speed-up-training) - Data visualization - Algorithm details - [FAQ](https://catboost.ai/docs/en/concepts/en/concepts/faq) - Educational materials - [Development and contributions](https://catboost.ai/docs/en/concepts/en/concepts/development-and-contributions) - [Contacts](https://catboost.ai/docs/en/concepts/en/concepts/contacts) Calculate metrics ## In this article: - [Purpose](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#purpose) - [Execution format](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#execution-format) - [Options](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#options) - [\-m, --model-file, --model-path](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#m,-model-file,-model-path) - [\--model-format](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#model-format) - [\--input-path](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#input-path) - [\--column-description, --cd](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#column-description,-cd) - [\--input-pairs](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#input-pairs) - [\--input-graph](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#input-graph) - [\-o, --output-path](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#o,-output-path) - [\-T, --thread-count](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#t,-thread-count) - [\--delimiter](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#delimiter) - [\--has-header](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#has-header) - [\--ntree-start](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#ntree-start) - [\--ntree-end](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#ntree-end) - [\--eval-period](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#eval-period) - [\--metrics](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#metrics) - [\--result-dir](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#result-dir) - [\--tmp-dir](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#tmp-dir) - [\--verbose](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#verbose) 1. Command-line version 2. Calculate metrics # Calculate metrics - [Purpose](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#purpose) - [Execution format](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#execution-format) - [Options](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#options) - [\-m, --model-file, --model-path](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#m,-model-file,-model-path) - [\--model-format](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#model-format) - [\--input-path](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#input-path) - [\--column-description, --cd](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#column-description,-cd) - [\--input-pairs](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#input-pairs) - [\--input-graph](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#input-graph) - [\-o, --output-path](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#o,-output-path) - [\-T, --thread-count](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#t,-thread-count) - [\--delimiter](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#delimiter) - [\--has-header](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#has-header) - [\--ntree-start](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#ntree-start) - [\--ntree-end](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#ntree-end) - [\--eval-period](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#eval-period) - [\--metrics](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#metrics) - [\--result-dir](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#result-dir) - [\--tmp-dir](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#tmp-dir) - [\--verbose](https://catboost.ai/docs/en/concepts/en/concepts/cli-reference_eval-metrics#verbose) ## Purpose Calculate metrics for a given dataset using a previously trained model. ## Execution format ``` catboost eval-metrics --metrics <comma-separated list of metrics> [optional parameters] ``` ## Options ### \-m, --model-file, --model-path #### Description The name of the input file with the description of the model obtained as the result of training. **Default value** model.bin ### \--model-format #### Description The format of the input model. Possible values: - CatboostBinary. - AppleCoreML (only datasets without categorical features are currently supported). - json (multiclassification models are not currently supported). Refer to the CatBoost [JSON model tutorial](https://github.com/catboost/tutorials/blob/master/model_analysis/model_export_as_json_tutorial.ipynb) for format details. **Default value** CatboostBinary ### \--input-path #### Description The name of the input file with the [dataset description](https://catboost.ai/docs/en/concepts/en/concepts/input-data_values-file). **Default value** input.tsv ### \--column-description, --cd #### Description The path to the input file that contains the [columns description](https://catboost.ai/docs/en/concepts/en/concepts/input-data_column-descfile). **Default value** If omitted, it is assumed that the first column in the file with the dataset description defines the label value, and the other columns are the values of numerical features. ### \--input-pairs #### Description The path to the input file that contains the pairs description for the dataset. This information is used for the calculation of Pairwise metrics. **Default value** Omitted Pairwise metrics require pairs of data. If this data is not provided explicitly by specifying this parameter, pairs are generated automatically in each group using object label values ### \--input-graph #### Description The path to the input file that contains the [graph information](https://catboost.ai/docs/en/concepts/en/concepts/input-data_graph-description) for the dataset. This information is used for calculation of [Graph aggregated features](https://catboost.ai/docs/en/concepts/en/features/graph-aggregated-features). **Default value** Omitted ### \-o, --output-path #### Description The path to the output file with [calculated metrics](https://catboost.ai/docs/en/concepts/en/concepts/output-data_loss-function). **Default value** output.tsv ### \-T, --thread-count #### Description The number of threads to calculate metrics. Optimizes the speed of execution. This parameter doesn't affect results. **Default value** The number of processor cores ### \--delimiter #### Description The delimiter character used to separate the data in the dataset description input file. Only single char delimiters are supported. If the specified value contains more than one character, only the first one is used. Note Used only if the dataset is given in the [Delimiter-separated values format](https://catboost.ai/docs/en/concepts/en/concepts/input-data_values-file). **Default value** The input data is assumed to be tab-separated ### \--has-header #### Description Read the column names from the first line of the dataset file if this parameter is set. Note Used only if the dataset is given in the [Delimiter-separated values format](https://catboost.ai/docs/en/concepts/en/concepts/input-data_values-file). **Default value** False (the first line is supposed to have the same data as the rest of them) ### \--ntree-start #### Description To reduce the number of trees to use when the model is applied or the metrics are calculated, set the range of the tree indices to `[--ntree-start; --ntree-end)` and the step of the trees to use to `--eval-period`. This parameter defines the index of the first tree to be used when applying the model or calculating the metrics (the inclusive left border of the range). Indices are zero-based. **Default value** 0 ### \--ntree-end #### Description To reduce the number of trees to use when the model is applied or the metrics are calculated, set the range of the tree indices to `[--ntree-start; --ntree-end)` and the step of the trees to use to `--eval-period`. This parameter defines the index of the first tree not to be used when applying the model or calculating the metrics (the exclusive right border of the range). Indices are zero-based. **Default value** 0 (the index of the last tree to use equals to the number of trees in the model minus one) ### \--eval-period #### Description To reduce the number of trees to use when the model is applied or the metrics are calculated, set the range of the tree indices to `[--ntree-start; --ntree-end)` and the step of the trees to use to `--eval-period`. This parameter defines the step to iterate over the range `[--ntree-start; --ntree-end)`. For example, let's assume that the following parameter values are set: - `--ntree-start` is set 0 - `--ntree-end` is set to N (the total tree count) - `--eval-period` is set to 2 In this case, the results are returned for the following tree ranges: `[0, 2), [0, 4), ... , [0, N)`. **Default value** 0 (the index of the last tree to use equals to the number of trees in the model minus one) ### \--metrics #### Description A comma-separated list of metrics to be calculated. [Possible values](https://catboost.ai/docs/en/concepts/en/references/custom-metric__supported-metrics) For example, if the AUC and Logloss metrics should be calculated, use the following construction: ``` --metrics AUC,Logloss ``` **Default value** Required parameter ### \--result-dir #### Description The directory for storing the files generated during metric calculation. **Default value** None (current directory) ### \--tmp-dir #### Description The directory for storing temporary files that are generated if non-additive metrics are calculated. By default, the directory is generated inside the current one at the start of calculation, and it is removed when the calculation is complete. Otherwise the specified value is used. **Default value** (the directory is generated) ### \--verbose #### Description Verbose output to stdout. **Default value** False ### Was the article helpful? 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## Purpose Calculate metrics for a given dataset using a previously trained model. ## Execution format ``` catboost eval-metrics --metrics <comma-separated list of metrics> [optional parameters] ``` ## Options ### \-m, --model-file, --model-path #### Description The name of the input file with the description of the model obtained as the result of training. **Default value** model.bin ### \--model-format #### Description The format of the input model. Possible values: - CatboostBinary. - AppleCoreML (only datasets without categorical features are currently supported). - json (multiclassification models are not currently supported). Refer to the CatBoost [JSON model tutorial](https://github.com/catboost/tutorials/blob/master/model_analysis/model_export_as_json_tutorial.ipynb) for format details. **Default value** CatboostBinary ### \--input-path #### Description The name of the input file with the [dataset description](https://catboost.ai/docs/en/concepts/input-data_values-file). **Default value** input.tsv ### \--column-description, --cd #### Description The path to the input file that contains the [columns description](https://catboost.ai/docs/en/concepts/input-data_column-descfile). **Default value** If omitted, it is assumed that the first column in the file with the dataset description defines the label value, and the other columns are the values of numerical features. ### \--input-pairs #### Description The path to the input file that contains the pairs description for the dataset. This information is used for the calculation of Pairwise metrics. **Default value** Omitted Pairwise metrics require pairs of data. If this data is not provided explicitly by specifying this parameter, pairs are generated automatically in each group using object label values ### \--input-graph #### Description The path to the input file that contains the [graph information](https://catboost.ai/docs/en/concepts/input-data_graph-description) for the dataset. This information is used for calculation of [Graph aggregated features](https://catboost.ai/docs/en/features/graph-aggregated-features). **Default value** Omitted ### \-o, --output-path #### Description The path to the output file with [calculated metrics](https://catboost.ai/docs/en/concepts/output-data_loss-function). **Default value** output.tsv ### \-T, --thread-count #### Description The number of threads to calculate metrics. Optimizes the speed of execution. This parameter doesn't affect results. **Default value** The number of processor cores ### \--delimiter #### Description The delimiter character used to separate the data in the dataset description input file. Only single char delimiters are supported. If the specified value contains more than one character, only the first one is used. **Default value** The input data is assumed to be tab-separated #### Description Read the column names from the first line of the dataset file if this parameter is set. **Default value** False (the first line is supposed to have the same data as the rest of them) ### \--ntree-start #### Description To reduce the number of trees to use when the model is applied or the metrics are calculated, set the range of the tree indices to `[--ntree-start; --ntree-end)` and the step of the trees to use to `--eval-period`. This parameter defines the index of the first tree to be used when applying the model or calculating the metrics (the inclusive left border of the range). Indices are zero-based. **Default value** 0 ### \--ntree-end #### Description To reduce the number of trees to use when the model is applied or the metrics are calculated, set the range of the tree indices to `[--ntree-start; --ntree-end)` and the step of the trees to use to `--eval-period`. This parameter defines the index of the first tree not to be used when applying the model or calculating the metrics (the exclusive right border of the range). Indices are zero-based. **Default value** 0 (the index of the last tree to use equals to the number of trees in the model minus one) ### \--eval-period #### Description To reduce the number of trees to use when the model is applied or the metrics are calculated, set the range of the tree indices to `[--ntree-start; --ntree-end)` and the step of the trees to use to `--eval-period`. This parameter defines the step to iterate over the range `[--ntree-start; --ntree-end)`. For example, let's assume that the following parameter values are set: - `--ntree-start` is set 0 - `--ntree-end` is set to N (the total tree count) - `--eval-period` is set to 2 In this case, the results are returned for the following tree ranges: `[0, 2), [0, 4), ... , [0, N)`. **Default value** 0 (the index of the last tree to use equals to the number of trees in the model minus one) ### \--metrics #### Description A comma-separated list of metrics to be calculated. [Possible values](https://catboost.ai/docs/en/references/custom-metric__supported-metrics) For example, if the AUC and Logloss metrics should be calculated, use the following construction: ``` --metrics AUC,Logloss ``` **Default value** Required parameter ### \--result-dir #### Description The directory for storing the files generated during metric calculation. **Default value** None (current directory) ### \--tmp-dir #### Description The directory for storing temporary files that are generated if non-additive metrics are calculated. By default, the directory is generated inside the current one at the start of calculation, and it is removed when the calculation is complete. Otherwise the specified value is used. **Default value** (the directory is generated) ### \--verbose #### Description Verbose output to stdout. **Default value** False