hillstrom

• Description:

This dataset contains 64,000 customers who last purchased within twelve months. The customers were involved in an e-mail test.

1. 1/3 were randomly chosen to receive an e-mail campaign featuring Mens merchandise.
2. 1/3 were randomly chosen to receive an e-mail campaign featuring Womens merchandise.
3. 1/3 were randomly chosen to not receive an e-mail campaign.

During a period of two weeks following the e-mail campaign, results were tracked. The task is to tell the world if the Mens or Womens e-mail campaign was successful.

• Homepage: https://blog.minethatdata.com/2008/03/minethatdata-e-mail-analytics-and-data.html

• Source code: tfds.recommendation.hillstrom.Hillstrom

• Versions:

  • 1.0.0 (default): Initial release.

• Download size: 3.78 MiB

• Dataset size: 15.87 MiB

• Auto-cached (documentation): Yes

• Splits:

Split	Examples
'train'	64,000

• Feature structure:

FeaturesDict({
    'channel': Text(shape=(), dtype=string),
    'conversion': int64,
    'history': float32,
    'history_segment': Text(shape=(), dtype=string),
    'mens': int64,
    'newbie': int64,
    'recency': int64,
    'segment': Text(shape=(), dtype=string),
    'spend': float32,
    'visit': int64,
    'womens': int64,
    'zip_code': Text(shape=(), dtype=string),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
channel	Text		string
conversion	Tensor		int64
history	Tensor		float32
history_segment	Text		string
mens	Tensor		int64
newbie	Tensor		int64
recency	Tensor		int64
segment	Text		string
spend	Tensor		float32
visit	Tensor		int64
womens	Tensor		int64
zip_code	Text		string

• Supervised keys (See as_supervised doc): ({'channel': 'channel', 'history': 'history', 'mens': 'mens', 'newbie': 'newbie', 'recency': 'recency', 'segment': 'segment', 'womens': 'womens', 'zip_code': 'zip_code'}, 'visit')

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe):

• Citation:

@article{entryhillstrom,
  title={Hillstrom’s MineThatData Email Analytics Challenge},
  author={ENTRY, WINNING}
}