Datasets:
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---
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` | |