---
metadata:
  - name: generator
    content: Diplodoc Platform v5.52.0
alternate:
  - https://catboost.ai/docs/en/concepts/python-reference_utils_get_fpr_curve.md
  - href: en/concepts/python-reference_utils_get_fpr_curve.md
    type: text/markdown
    title: Markdown version
  - href: ../llms.txt
    type: text/markdown
    title: llms.txt
---
> **Documentation Index:** Fetch the complete configuration index at https://catboost.ai/docs/en/llms.txt

# get_fpr_curve

<!-- source: en/_includes/work_src/reusage-python/get_fpr_curve__desc.md -->
Return points of the FPR curve.
<!-- endsource: en/_includes/work_src/reusage-python/get_fpr_curve__desc.md -->


## Method call format {#call-format}

```python
get_fpr_curve(model=None,
              data=None,
              curve=None,
              thread_count=-1,
              plot=False)
```

## Parameters {#parameters}

### model

#### Description

The trained model.

**Possible types**

catboost.CatBoost

**Default value**

None

### data

#### Description

A set of samples to build the FPR curve with.

Should not be used with the `curve` parameter.

**Possible types**

- catboost.Pool
- list of catboost.Pool

**Default value**

None

### curve

#### Description

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](https://catboost.ai/docs/en/concepts/python-reference_utils_get_roc_curve.md) function as the value of this parameter.

The input data must certain criteria:

- The threshold values should not increase.
- There should not be any repetitions of the fpr-tpr- threshold triplets.


**Possible types**

tuple of three arrays (fpr, tpr, thresholds)

**Default value**

None

### thread_count

#### Description

The number of threads to use.

Optimizes the speed of execution. This parameter doesn't affect results.

**Possible types**

int

**Default value**

-1 (the number of threads is equal to the number of processor cores)

### plot

#### Description

Plot a chart based on the found points.

**Possible types**

bool

**Default value**

False



## Type of return value {#output-format}

tuple of two arrays (thresholds, fpr)

## Usage examples {#usage-examples}

```python
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, plot=True)
print(thresholds)
print(fpr)
```

Output:

```bash
[1.         0.55302101 0.5508888  0.50891881 0.        ]
[0. 0. 0. 0. 1.]
```