---
language:
- en
tags:
- nbfi
- tabular_classification
- binary_classification
pretty_name: NBFI
size_categories:
- 1K<n<10K
task_categories:
- tabular-classification
configs:
- default
license: cc
---
# NBFI
The [NBFI dataset](https://www.kaggle.com/datasets/meastanmay/nbfi-vehicle-loan-repayment-dataset) from the [Kaggle](https://www.kaggle.com/datasets).
Client default prediction.

| **Configuration** | **Task**                  | **Description**                                                 |
|-------------------|---------------------------|-----------------------------------------------------------------|
| default           | Binary classification     | Has the client defaulted?                                       |

# Usage
```python
from datasets import load_dataset

dataset = load_dataset("mstz/nbfi")["train"]
```


# Features
|**Feature**                                    |**Type**       |
|-----------------------------------------------|---------------|
|`income`                                       | `float32`     |
|`owns_a_car`                                   | `bool`        |
|`owns_a_bike`                                  | `bool`        |
|`has_an_active_loan`                           | `bool`        |
|`owns_a_house`                                 | `bool`        |
|`nr_children`                                  | `int8`        |
|`credit`                                       | `float32`     |
|`loan_annuity`                                 | `float32`     |
|`accompanied_by`                               | `string`      |
|`income_type`                                  | `string`      |
|`education_level`                              | `float32`     |
|`marital_status`                               | `float32`     |
|`is_male`                                      | `bool`        |
|`type_of_contract`                             | `string`      |
|`type_of_housing`                              | `string`      |
|`residence_density`                            | `float32`     |
|`age_in_days`                                  | `int32`       |
|`consecutive_days_of_employment`               | `int16`       |
|`nr_days_since_last_registration_change`       | `int32`       |
|`nr_days_since_last_document_change`           | `int32`       |
|`owned_a_house_for_nr_days`                    | `int32`       |
|`has_provided_a_mobile_number`                 | `bool`        |
|`has_provided_a_home_number`                   | `bool`        |
|`was_reachable_at_work`                        | `bool`        |
|`job`                                          | `string`      |
|`nr_family_members`                            | `int8`        |
|`city_rating`                                  | `int8`        |
|`weekday_of_application`                       | `int8`        |
|`hour_of_application`                          | `float32`     |
|`same_residence_and_home`                      | `bool`        |
|`same_work_and_home`                           | `bool`        |
|`score_1`                                      | `float32`     |
|`score_2`                                      | `float32`     |
|`score_3`                                      | `float32`     |
|`nr_defaults_in_social_circle`                 | `int8`        |
|`inquiries_in_last_year`                       | `float32`     |