cvmodel
cv_model(config, fun_control)
¶
Performs k-fold cross-validation on a model using the given configuration and function control parameters.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
config |
dict
|
A dictionary containing the configuration parameters for the model. |
required |
fun_control |
dict
|
A dictionary containing the function control parameters. |
required |
Returns:
Type | Description |
---|---|
float
|
The mean average precision at k (MAP@k) score of the model. |
Examples:
>>> config = {
... "initialization": "Xavier",
... "batch_size": 32,
... "patience": 10,
... }
>>> fun_control = {
... "_L_in": 10,
... "_L_out": 1,
... "_L_cond": 0,
... "enable_progress_bar": True,
... "core_model": MyModel,
... "num_workers": 4,
... "DATASET_PATH": "./data",
... "CHECKPOINT_PATH": "./checkpoints",
... "TENSORBOARD_PATH": "./tensorboard",
... "k_folds": 5,
... }
>>> mapk_score = cv_model(config, fun_control)
Source code in spotpython/light/cvmodel.py
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