istella

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  • Description:

The Istella datasets are three large-scale Learning-to-Rank datasets released by Istella. Each dataset consists of query-document pairs represented as feature vectors and corresponding relevance judgment labels.

The dataset contains three versions:

  • main ("Istella LETOR"): Containing 10,454,629 query-document pairs.
  • s ("Istella-S LETOR"): Containing 3,408,630 query-document pairs.
  • x ("Istella-X LETOR"): Containing 26,791,447 query-document pairs.

You can specify whether to use the main, s or x version of the dataset as follows:

ds = tfds.load("istella/main")
ds = tfds.load("istella/s")
ds = tfds.load("istella/x")

If only istella is specified, the istella/main option is selected by default:

# This is the same as `tfds.load("istella/main")`
ds = tfds.load("istella")
FeaturesDict({
    'float_features': Tensor(shape=(None, 220), dtype=tf.float64),
    'label': Tensor(shape=(None,), dtype=tf.float64),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
float_features Tensor (None, 220) tf.float64
label Tensor (None,) tf.float64
@article{10.1145/2987380,
  author = {Dato, Domenico and Lucchese, Claudio and Nardini, Franco Maria and Orlando, Salvatore and Perego, Raffaele and Tonellotto, Nicola and Venturini, Rossano},
  title = {Fast Ranking with Additive Ensembles of Oblivious and Non-Oblivious Regression Trees},
  year = {2016},
  publisher = {ACM},
  address = {New York, NY, USA},
  volume = {35},
  number = {2},
  issn = {1046-8188},
  url = {https://doi.org/10.1145/2987380},
  doi = {10.1145/2987380},
  journal = {ACM Transactions on Information Systems},
  articleno = {15},
  numpages = {31},
}

istella/main (default config)

  • Download size: 1.20 GiB

  • Dataset size: 1.10 GiB

  • Splits:

Split Examples
'test' 9,799
'train' 23,219

istella/s

  • Download size: 450.26 MiB

  • Dataset size: 414.69 MiB

  • Splits:

Split Examples
'test' 6,562
'train' 19,245
'vali' 7,211

istella/x

  • Download size: 4.42 GiB

  • Dataset size: 2.42 GiB

  • Splits:

Split Examples
'test' 2,000
'train' 6,000
'vali' 2,000