# Speed dating
The [Speed dating dataset](https://www.openml.org/search?type=data&sort=nr_of_likes&status=active&id=40536) from OpenML.


# Configurations and tasks
| **Configuration** | **Task**                  | Description                                                   |
|-------------------|---------------------------|---------------------------------------------------------------|
| dating            | Binary classification     | Will the two date?                                            |

# Usage
```python
from datasets import load_dataset

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


# Features
|**Features**                                       |**Type** |
|---------------------------------------------------|---------|
|`is_dater_male`                                    |`int8`   |
|`dater_age`                                        |`int8`   |
|`dated_age`                                        |`int8`   |
|`age_difference`                                   |`int8`   |
|`dater_race`                                       |`string` |
|`dated_race`                                       |`string` |
|`are_same_race`                                    |`int8`   |
|`same_race_importance_for_dater`                   |`float64`|
|`same_religion_importance_for_dater`               |`float64`|
|`attractiveness_importance_for_dated`              |`float64`|
|`sincerity_importance_for_dated`                   |`float64`|
|`intelligence_importance_for_dated`                |`float64`|
|`humor_importance_for_dated`                       |`float64`|
|`ambition_importance_for_dated`                    |`float64`|
|`shared_interests_importance_for_dated`            |`float64`|
|`attractiveness_score_of_dater_from_dated`         |`float64`|
|`sincerity_score_of_dater_from_dated`              |`float64`|
|`intelligence_score_of_dater_from_dated`           |`float64`|
|`humor_score_of_dater_from_dated`                  |`float64`|
|`ambition_score_of_dater_from_dated`               |`float64`|
|`shared_interests_score_of_dater_from_dated`       |`float64`|
|`attractiveness_importance_for_dater`              |`float64`|
|`sincerity_importance_for_dater`                   |`float64`|
|`intelligence_importance_for_dater`                |`float64`|
|`humor_importance_for_dater`                       |`float64`|
|`ambition_importance_for_dater`                    |`float64`|
|`shared_interests_importance_for_dater`            |`float64`|
|`self_reported_attractiveness_of_dater`            |`float64`|
|`self_reported_sincerity_of_dater`                 |`float64`|
|`self_reported_intelligence_of_dater`              |`float64`|
|`self_reported_humor_of_dater`                     |`float64`|
|`self_reported_ambition_of_dater`                  |`float64`|
|`reported_attractiveness_of_dated_from_dater`      |`float64`|
|`reported_sincerity_of_dated_from_dater`           |`float64`|
|`reported_intelligence_of_dated_from_dater`        |`float64`|
|`reported_humor_of_dated_from_dater`               |`float64`|
|`reported_ambition_of_dated_from_dater`            |`float64`|
|`reported_shared_interests_of_dated_from_dater`    |`float64`|
|`dater_interest_in_sports`                         |`float64`|
|`dater_interest_in_tvsports`                       |`float64`|
|`dater_interest_in_exercise`                       |`float64`|
|`dater_interest_in_dining`                         |`float64`|
|`dater_interest_in_museums`                        |`float64`|
|`dater_interest_in_art`                            |`float64`|
|`dater_interest_in_hiking`                         |`float64`|
|`dater_interest_in_gaming`                         |`float64`|
|`dater_interest_in_clubbing`                       |`float64`|
|`dater_interest_in_reading`                        |`float64`|
|`dater_interest_in_tv`                             |`float64`|
|`dater_interest_in_theater`                        |`float64`|
|`dater_interest_in_movies`                         |`float64`|
|`dater_interest_in_concerts`                       |`float64`|
|`dater_interest_in_music`                          |`float64`|
|`dater_interest_in_shopping`                       |`float64`|
|`dater_interest_in_yoga`                           |`float64`|
|`interests_correlation`                            |`float64`|
|`expected_satisfaction_of_dater`                   |`float64`|
|`expected_number_of_likes_of_dater_from_20_people` |`int8`   |
|`expected_number_of_dates_for_dater`               |`int8`   |
|`dater_liked_dated`                                |`float64`|
|`probability_dated_wants_to_date`                  |`float64`|
|`already_met_before`                               |`int8`   |
|`dater_wants_to_date`                              |`int8`   |
|`dated_wants_to_date`                              |`int8`   |

task_categories:tabular-classification size_categories:1K<n<10K language:en speeddating tabular_classification binary_classification region:us
{"language": ["en"], "size_categories": ["1K<n<10K"], "task_categories": ["tabular-classification"], "pretty_name": "Speed dating", "tags": ["speeddating", "tabular_classification", "binary_classification"], "configs": ["dating"]}
TAGS
#task_categories-tabular-classification #size_categories-1K<n<10K #language-English #speeddating #tabular_classification #binary_classification #region-us 

Speed dating
============


The Speed dating dataset from OpenML.


Configurations and tasks
========================


Configuration: dating, Task: Binary classification, Description: Will the two date?


Usage
=====


Features
========




TAGS
#task_categories-tabular-classification #size_categories-1K<n<10K #language-English #speeddating #tabular_classification #binary_classification #region-us 

passage: TAGS
#task_categories-tabular-classification #size_categories-1K<n<10K #language-English #speeddating #tabular_classification #binary_classification #region-us 
