Bu sayfa, Cloud Translation API ile çevrilmiştir.

istella

Açıklama :

Istella veri kümeleri, Istella tarafından yayınlanan üç büyük ölçekli Derecelendirmeyi Öğrenen veri kümesidir. Her veri kümesi, özellik vektörleri ve ilgili uygunluk değerlendirme etiketleri olarak temsil edilen sorgu-belge çiftlerinden oluşur.

Veri kümesi üç sürüm içerir:

main ("Istella LETOR"): 10.454.629 sorgu-belge çifti içerir.
s ("Istella-S LETOR"): 3.408.630 sorgu-belge çifti içerir.
x ("Istella-X LETOR"): 26.791.447 sorgu-belge çifti içerir.

Veri kümesinin main , s veya x sürümünün kullanılıp kullanılmayacağını aşağıdaki gibi belirleyebilirsiniz:

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

Yalnızca istella belirtilmişse, varsayılan olarak istella/main seçeneği seçilidir:

# This is the same as `tfds.load("istella/main")`
ds = tfds.load("istella")

Ana sayfa : http://quickrank.isti.cnr.it/istella-dataset/
Kaynak kodu : tfds.ranking.istella.Istella
Sürümler :
- 1.0.0 : İlk sürüm.
- 1.0.1 (varsayılan): Float64'ü desteklemek için serileştirmeyi düzeltin.
Otomatik önbelleğe alınmış ( belgeler ): Hayır
Özellikler :

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    'feature_92': Tensor(shape=(None,), dtype=tf.float64),
    'feature_93': Tensor(shape=(None,), dtype=tf.float64),
    'feature_94': Tensor(shape=(None,), dtype=tf.float64),
    'feature_95': Tensor(shape=(None,), dtype=tf.float64),
    'feature_96': Tensor(shape=(None,), dtype=tf.float64),
    'feature_97': Tensor(shape=(None,), dtype=tf.float64),
    'feature_98': Tensor(shape=(None,), dtype=tf.float64),
    'feature_99': Tensor(shape=(None,), dtype=tf.float64),
    'label': Tensor(shape=(None,), dtype=tf.float64),
})

Denetimli anahtarlar (bkz as_supervised doc ): None
Şekil ( tfds.show_examples ): Desteklenmez.
alıntı :

@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 (varsayılan yapılandırma)

İndirme boyutu : 1.20 GiB
Veri kümesi boyutu : 1.40 GiB
Bölmeler :

Bölmek	Örnekler
`'test'`	9,799
`'train'`	23.219

Örnekler ( tfds.as_dataframe ):

istella/lar

İndirme boyutu : 450.26 MiB
Veri kümesi boyutu : 728.40 MiB
Bölmeler :

Bölmek	Örnekler
`'test'`	6.562
`'train'`	19.245
`'vali'`	7.211

Örnekler ( tfds.as_dataframe ):

istella/x

İndirme boyutu : 4.42 GiB
Veri kümesi boyutu : 2.06 GiB
Bölmeler :

Bölmek	Örnekler
`'test'`	2.000
`'train'`	6.000
`'vali'`	2.000

Örnekler ( tfds.as_dataframe ):