lightgbm.CVBooster

class lightgbm.CVBooster(model_file=None)[source]

Bases: object

CVBooster in LightGBM.

Auxiliary data structure to hold and redirect all boosters of cv() function. This class has the same methods as Booster class. All method calls, except for the following methods, are actually performed for underlying Boosters and then all returned results are returned in a list.

model_from_string()
model_to_string()
save_model()

boosters

The list of underlying fitted models.

Type:: list of Booster

best_iteration

The best iteration of fitted model.

Type:: int

__init__(model_file=None)[source]

Initialize the CVBooster.

Parameters:: model_file (str, pathlib.Path or None, optional (default=None)) – Path to the CVBooster model file.

Methods

`__init__`([model_file])	Initialize the CVBooster.
`model_from_string`(model_str)	Load CVBooster from a string.
`model_to_string`([num_iteration, ...])	Save CVBooster to JSON string.
`save_model`(filename[, num_iteration, ...])	Save CVBooster to a file as JSON text.

model_from_string(model_str)[source]

Load CVBooster from a string.

Parameters:: model_str (str) – Model will be loaded from this string.
Returns:: self – Loaded CVBooster object.
Return type:: CVBooster

model_to_string(num_iteration=None, start_iteration=0, importance_type='split')[source]

Save CVBooster to JSON string.

Parameters:

num_iteration (int or None, optional (default=None)) – Index of the iteration that should be saved. If None, if the best iteration exists, it is saved; otherwise, all iterations are saved. If <= 0, all iterations are saved.
start_iteration (int, optional (default=0)) – Start index of the iteration that should be saved.
importance_type (str, optional (default="split")) – What type of feature importance should be saved. If “split”, result contains numbers of times the feature is used in a model. If “gain”, result contains total gains of splits which use the feature.

Returns:

str_repr – JSON string representation of CVBooster.

Return type:

str

save_model(filename, num_iteration=None, start_iteration=0, importance_type='split')[source]

Save CVBooster to a file as JSON text.

Parameters:

filename (str or pathlib.Path) – Filename to save CVBooster.
num_iteration (int or None, optional (default=None)) – Index of the iteration that should be saved. If None, if the best iteration exists, it is saved; otherwise, all iterations are saved. If <= 0, all iterations are saved.
start_iteration (int, optional (default=0)) – Start index of the iteration that should be saved.
importance_type (str, optional (default="split")) – What type of feature importance should be saved. If “split”, result contains numbers of times the feature is used in a model. If “gain”, result contains total gains of splits which use the feature.

Returns:

self – Returns self.

Return type:

CVBooster