get_fpr_curve
Return points of the FPR curve.
Method call format
get_fpr_curve(model=None,
data=None,
curve=None,
thread_count=-1)
Parameters
Parameter | Possible types | Description | Default value |
---|---|---|---|
model | catboost.CatBoost | The trained model. | None |
data |
| A set of samples to build the FPR curve with. Should not be used with the curve parameter. | None |
curve | tuple of three arrays (fpr, tpr, thresholds) | ROC curve points. Should not be used with the data parameter. Required if the data and model parameters are set to None. It is strictly recommended to use the output of the get_roc_curve function as the value of this parameter.
The input data must meet the following criteria: | None |
thread_count | int | The number of threads to use. Optimizes the speed of execution. This parameter doesn't affect results. | -1 (the number of threads is equal to the number of processor cores) |
Parameter | Possible types | Description | Default value |
---|---|---|---|
model | catboost.CatBoost | The trained model. | None |
data |
| A set of samples to build the FPR curve with. Should not be used with the curve parameter. | None |
curve | tuple of three arrays (fpr, tpr, thresholds) | ROC curve points. Should not be used with the data parameter. Required if the data and model parameters are set to None. It is strictly recommended to use the output of the get_roc_curve function as the value of this parameter.
The input data must meet the following criteria: | None |
thread_count | int | The number of threads to use. Optimizes the speed of execution. This parameter doesn't affect results. | -1 (the number of threads is equal to the number of processor cores) |
Type of return value
tuple of two arrays (thresholds, fpr)
Usage examples
from catboost import CatBoostClassifier, Pool
from catboost.utils import get_roc_curve, get_fpr_curve
train_data = [[1,3],
[0,4],
[1,7],
[3,0]]
train_labels = [1,0,1,1]
catboost_pool = Pool(train_data, train_labels)
model = CatBoostClassifier(learning_rate=0.03)
model.fit(train_data, train_labels, verbose=False)
roc_curve_values = get_roc_curve(model, catboost_pool)
(thresholds, fpr) = get_fpr_curve(curve=roc_curve_values)
print(thresholds)
print(fpr)