german_credit_numeric

• Description:

This dataset classifies people described by a set of attributes as good or bad credit risks. The version here is the "numeric" variant where categorical and ordered categorical attributes have been encoded as indicator and integer quantities respectively.

• Homepage: https://archive.ics.uci.edu/ml/datasets/Statlog+(German+Credit+Data)

• Source code: tfds.structured.GermanCreditNumeric

• Versions:

  • 1.0.0 (default): No release notes.

• Download size: 99.61 KiB

• Dataset size: 58.61 KiB

• Auto-cached (documentation): Yes

• Splits:

• Feature structure:

FeaturesDict({
    'features': Tensor(shape=(24,), dtype=int32),
    'label': ClassLabel(shape=(), dtype=int64, num_classes=2),
})

• Feature documentation:

• Supervised keys (See as_supervised doc): ('features', 'label')

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe):

• Citation:

@misc{Dua:2019 ,
author = "Dua, Dheeru and Graff, Casey",
year = "2017",
title = "{UCI} Machine Learning Repository",
url = "http://archive.ics.uci.edu/ml",
institution = "University of California, Irvine, School of Information and Computer Sciences"
}