Output settings
logging_level
Command line: --logging-level
Description
The logging level to output to stdout.
Possible values:
-
Silent — Do not output any logging information to stdout.
-
Verbose — Output the following data to stdout:
- optimized metric
- elapsed time of training
- remaining time of training
-
Info — Output additional information and the number of trees.
-
Debug — Output debugging information.
Type
string
Default value
Python package
None (corresponds to the Verbose logging level)
R package, Command-line
Verbose
Supported processing units
CPU and GPU
metric_period
Command line: --metric-period
Description
The frequency of iterations to calculate the values of objectives and metrics. The value should be a positive integer.
The usage of this parameter speeds up the training.
Python package, Command-line
Note
It is recommended to increase the value of this parameter to maintain training speed if a GPU processing unit type is used.
Type
int
Default value
1
Supported processing units
CPU and GPU
verbose
Command line: --verbose
Alias:verbose_eval
Description
The purpose of this parameter depends on the type of the given value:
-
bool — Defines the logging level:
True
corresponds to the Verbose logging levelFalse
corresponds to the Silent logging level
-
int — Use the Verbose logging level and set the logging period to the value of this parameter.
Python package, R package
Alert
Do not use this parameter with the logging_level parameter.
Command-line
Alert
Do not use this parameter with the --logging-level parameter.
Type
- bool
- int
Default value
1
Supported processing units
CPU and GPU
train_dir
Command line: --train-dir
Description
The directory for storing the files generated during training.
Type
string
Default value
Python package, R package
catboost_info
Command-line
Current directory
Supported processing units
CPU and GPU
model_size_reg
Command line: --model-size-reg
Description
The model size regularization coefficient. The larger the value, the smaller the model size. Refer to the Model size regularization coefficient section for details.
Possible values are in the range .
This regularization is needed only for models with categorical features (other models are small). Models with categorical features might weight tens of gigabytes or more if categorical features have a lot of values. If the value of the regularizer differs from zero, then the usage of categorical features or feature combinations with a lot of values has a penalty, so less of them are used in the resulting model.
Note that the resulting quality of the model can be affected. Set the value to 0 to turn off the model size optimization option.
Type
float
Default value
Python package
None (Turned on and set to 0.5)
R package, Command-line
Turned on and set to 0.5
Supported processing units CPU and GPU
allow_writing_files
Description
Allow to write analytical and snapshot files during training.
If set to False
, the snapshot and data visualization tools are unavailable.
Type
bool
Default value
True
Supported processing units
CPU and GPU
save_snapshot
Description
Enable snapshotting for restoring the training progress after an interruption. If enabled, the default period for making snapshots is 600 seconds. Use the snapshot_interval parameter to change this period.
Note
This parameter is not supported in the params parameter of the cv function.
Type
bool
Default value
None
Supported processing units
CPU and GPU
snapshot_file
Description
The name of the file to save the training progress information in. This file is used for recovering training after an interruption.
Depending on whether the specified file exists in the file system:
- Missing — Write information about training progress to the specified file.
- Exists — Load data from the specified file and continue training from where it left off.
Note
This parameter is not supported in the params parameter of the cv function.
Type
string
Default value
experiment...
experiment.cbsnapshot
Supported processing units
CPU and GPU
snapshot_interval
Description
The interval between saving snapshots in seconds.
The first snapshot is taken after the specified number of seconds since the start of training. Every subsequent snapshot is taken after the specified number of seconds since the previous one. The last snapshot is taken at the end of the training.
Note
This parameter is not supported in the params parameter of the cv function.
Type
int
Default value
600
Supported processing units
CPU and GPU
roc_file
Description
The name of the output file to save the ROC curve points to. This parameter can only be set in cross-validation mode if the Logloss loss function is selected. The ROC curve points are calculated for the test fold.
The output file is saved to the catboost_info directory.
Type
string
Default value
None (the file is not saved)
Supported processing units
CPU and GPU