mslr_web

  • Açıklama :

MSLR-WEB, Microsoft Research tarafından yayınlanan iki büyük ölçekli Dereceye Göre Öğrenme veri kümesidir. İlk veri kümesi ("30k" olarak adlandırılır) 30.000 sorgu içerir ve ikinci veri kümesi ("10k" olarak adlandırılır) 10.000 sorgu içerir. Her veri kümesi, özellik vektörleri ve ilgili uygunluk değerlendirme etiketleri olarak temsil edilen sorgu-belge çiftlerinden oluşur.

Veri kümesinin "10k" veya "30k" sürümünün kullanılıp kullanılmayacağını ve buna karşılık gelen bir katlamayı aşağıdaki gibi belirleyebilirsiniz:

ds = tfds.load("mslr_web/30k_fold1")

Yalnızca mslr_web belirtilirse, varsayılan olarak mslr_web/10k_fold1 seçeneği seçilir:

# This is the same as `tfds.load("mslr_web/10k_fold1")`
ds = tfds.load("mslr_web")
FeaturesDict({
    'bm25_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'bm25_body': Tensor(shape=(None,), dtype=tf.float64),
    'bm25_title': Tensor(shape=(None,), dtype=tf.float64),
    'bm25_url': Tensor(shape=(None,), dtype=tf.float64),
    'bm25_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'boolean_model_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'boolean_model_body': Tensor(shape=(None,), dtype=tf.float64),
    'boolean_model_title': Tensor(shape=(None,), dtype=tf.float64),
    'boolean_model_url': Tensor(shape=(None,), dtype=tf.float64),
    'boolean_model_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'covered_query_term_number_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'covered_query_term_number_body': Tensor(shape=(None,), dtype=tf.float64),
    'covered_query_term_number_title': Tensor(shape=(None,), dtype=tf.float64),
    'covered_query_term_number_url': Tensor(shape=(None,), dtype=tf.float64),
    'covered_query_term_number_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'covered_query_term_ratio_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'covered_query_term_ratio_body': Tensor(shape=(None,), dtype=tf.float64),
    'covered_query_term_ratio_title': Tensor(shape=(None,), dtype=tf.float64),
    'covered_query_term_ratio_url': Tensor(shape=(None,), dtype=tf.float64),
    'covered_query_term_ratio_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'idf_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'idf_body': Tensor(shape=(None,), dtype=tf.float64),
    'idf_title': Tensor(shape=(None,), dtype=tf.float64),
    'idf_url': Tensor(shape=(None,), dtype=tf.float64),
    'idf_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'inlink_number': Tensor(shape=(None,), dtype=tf.float64),
    'label': Tensor(shape=(None,), dtype=tf.float64),
    'length_of_url': Tensor(shape=(None,), dtype=tf.float64),
    'lmir_abs_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'lmir_abs_body': Tensor(shape=(None,), dtype=tf.float64),
    'lmir_abs_title': Tensor(shape=(None,), dtype=tf.float64),
    'lmir_abs_url': Tensor(shape=(None,), dtype=tf.float64),
    'lmir_abs_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'lmir_dir_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'lmir_dir_body': Tensor(shape=(None,), dtype=tf.float64),
    'lmir_dir_title': Tensor(shape=(None,), dtype=tf.float64),
    'lmir_dir_url': Tensor(shape=(None,), dtype=tf.float64),
    'lmir_dir_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'lmir_jm_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'lmir_jm_body': Tensor(shape=(None,), dtype=tf.float64),
    'lmir_jm_title': Tensor(shape=(None,), dtype=tf.float64),
    'lmir_jm_url': Tensor(shape=(None,), dtype=tf.float64),
    'lmir_jm_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'max_of_stream_length_normalized_term_frequency_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'max_of_stream_length_normalized_term_frequency_body': Tensor(shape=(None,), dtype=tf.float64),
    'max_of_stream_length_normalized_term_frequency_title': Tensor(shape=(None,), dtype=tf.float64),
    'max_of_stream_length_normalized_term_frequency_url': Tensor(shape=(None,), dtype=tf.float64),
    'max_of_stream_length_normalized_term_frequency_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'max_of_term_frequency_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'max_of_term_frequency_body': Tensor(shape=(None,), dtype=tf.float64),
    'max_of_term_frequency_title': Tensor(shape=(None,), dtype=tf.float64),
    'max_of_term_frequency_url': Tensor(shape=(None,), dtype=tf.float64),
    'max_of_term_frequency_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'max_of_tf_idf_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'max_of_tf_idf_body': Tensor(shape=(None,), dtype=tf.float64),
    'max_of_tf_idf_title': Tensor(shape=(None,), dtype=tf.float64),
    'max_of_tf_idf_url': Tensor(shape=(None,), dtype=tf.float64),
    'max_of_tf_idf_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'mean_of_stream_length_normalized_term_frequency_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'mean_of_stream_length_normalized_term_frequency_body': Tensor(shape=(None,), dtype=tf.float64),
    'mean_of_stream_length_normalized_term_frequency_title': Tensor(shape=(None,), dtype=tf.float64),
    'mean_of_stream_length_normalized_term_frequency_url': Tensor(shape=(None,), dtype=tf.float64),
    'mean_of_stream_length_normalized_term_frequency_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'mean_of_term_frequency_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'mean_of_term_frequency_body': Tensor(shape=(None,), dtype=tf.float64),
    'mean_of_term_frequency_title': Tensor(shape=(None,), dtype=tf.float64),
    'mean_of_term_frequency_url': Tensor(shape=(None,), dtype=tf.float64),
    'mean_of_term_frequency_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'mean_of_tf_idf_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'mean_of_tf_idf_body': Tensor(shape=(None,), dtype=tf.float64),
    'mean_of_tf_idf_title': Tensor(shape=(None,), dtype=tf.float64),
    'mean_of_tf_idf_url': Tensor(shape=(None,), dtype=tf.float64),
    'mean_of_tf_idf_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'min_of_stream_length_normalized_term_frequency_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'min_of_stream_length_normalized_term_frequency_body': Tensor(shape=(None,), dtype=tf.float64),
    'min_of_stream_length_normalized_term_frequency_title': Tensor(shape=(None,), dtype=tf.float64),
    'min_of_stream_length_normalized_term_frequency_url': Tensor(shape=(None,), dtype=tf.float64),
    'min_of_stream_length_normalized_term_frequency_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'min_of_term_frequency_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'min_of_term_frequency_body': Tensor(shape=(None,), dtype=tf.float64),
    'min_of_term_frequency_title': Tensor(shape=(None,), dtype=tf.float64),
    'min_of_term_frequency_url': Tensor(shape=(None,), dtype=tf.float64),
    'min_of_term_frequency_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'min_of_tf_idf_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'min_of_tf_idf_body': Tensor(shape=(None,), dtype=tf.float64),
    'min_of_tf_idf_title': Tensor(shape=(None,), dtype=tf.float64),
    'min_of_tf_idf_url': Tensor(shape=(None,), dtype=tf.float64),
    'min_of_tf_idf_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'number_of_slash_in_url': Tensor(shape=(None,), dtype=tf.float64),
    'outlink_number': Tensor(shape=(None,), dtype=tf.float64),
    'page_rank': Tensor(shape=(None,), dtype=tf.float64),
    'quality_score': Tensor(shape=(None,), dtype=tf.float64),
    'quality_score_2': Tensor(shape=(None,), dtype=tf.float64),
    'query_url_click_count': Tensor(shape=(None,), dtype=tf.float64),
    'site_rank': Tensor(shape=(None,), dtype=tf.float64),
    'stream_length_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'stream_length_body': Tensor(shape=(None,), dtype=tf.float64),
    'stream_length_title': Tensor(shape=(None,), dtype=tf.float64),
    'stream_length_url': Tensor(shape=(None,), dtype=tf.float64),
    'stream_length_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'sum_of_stream_length_normalized_term_frequency_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'sum_of_stream_length_normalized_term_frequency_body': Tensor(shape=(None,), dtype=tf.float64),
    'sum_of_stream_length_normalized_term_frequency_title': Tensor(shape=(None,), dtype=tf.float64),
    'sum_of_stream_length_normalized_term_frequency_url': Tensor(shape=(None,), dtype=tf.float64),
    'sum_of_stream_length_normalized_term_frequency_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'sum_of_term_frequency_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'sum_of_term_frequency_body': Tensor(shape=(None,), dtype=tf.float64),
    'sum_of_term_frequency_title': Tensor(shape=(None,), dtype=tf.float64),
    'sum_of_term_frequency_url': Tensor(shape=(None,), dtype=tf.float64),
    'sum_of_term_frequency_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'sum_of_tf_idf_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'sum_of_tf_idf_body': Tensor(shape=(None,), dtype=tf.float64),
    'sum_of_tf_idf_title': Tensor(shape=(None,), dtype=tf.float64),
    'sum_of_tf_idf_url': Tensor(shape=(None,), dtype=tf.float64),
    'sum_of_tf_idf_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'url_click_count': Tensor(shape=(None,), dtype=tf.float64),
    'url_dwell_time': Tensor(shape=(None,), dtype=tf.float64),
    'variance_of_stream_length_normalized_term_frequency_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'variance_of_stream_length_normalized_term_frequency_body': Tensor(shape=(None,), dtype=tf.float64),
    'variance_of_stream_length_normalized_term_frequency_title': Tensor(shape=(None,), dtype=tf.float64),
    'variance_of_stream_length_normalized_term_frequency_url': Tensor(shape=(None,), dtype=tf.float64),
    'variance_of_stream_length_normalized_term_frequency_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'variance_of_term_frequency_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'variance_of_term_frequency_body': Tensor(shape=(None,), dtype=tf.float64),
    'variance_of_term_frequency_title': Tensor(shape=(None,), dtype=tf.float64),
    'variance_of_term_frequency_url': Tensor(shape=(None,), dtype=tf.float64),
    'variance_of_term_frequency_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'variance_of_tf_idf_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'variance_of_tf_idf_body': Tensor(shape=(None,), dtype=tf.float64),
    'variance_of_tf_idf_title': Tensor(shape=(None,), dtype=tf.float64),
    'variance_of_tf_idf_url': Tensor(shape=(None,), dtype=tf.float64),
    'variance_of_tf_idf_whole_document': Tensor(shape=(None,), dtype=tf.float64),
    'vector_space_model_anchor': Tensor(shape=(None,), dtype=tf.float64),
    'vector_space_model_body': Tensor(shape=(None,), dtype=tf.float64),
    'vector_space_model_title': Tensor(shape=(None,), dtype=tf.float64),
    'vector_space_model_url': Tensor(shape=(None,), dtype=tf.float64),
    'vector_space_model_whole_document': Tensor(shape=(None,), dtype=tf.float64),
})
@article{DBLP:journals/corr/QinL13,
  author    = {Tao Qin and Tie{-}Yan Liu},
  title     = {Introducing {LETOR} 4.0 Datasets},
  journal   = {CoRR},
  volume    = {abs/1306.2597},
  year      = {2013},
  url       = {http://arxiv.org/abs/1306.2597},
  timestamp = {Mon, 01 Jul 2013 20:31:25 +0200},
  biburl    = {http://dblp.uni-trier.de/rec/bib/journals/corr/QinL13},
  bibsource = {dblp computer science bibliography, http://dblp.org}
}

mslr_web/10k_fold1 (varsayılan yapılandırma)

  • İndirme boyutu : 1.15 GiB

  • Veri kümesi boyutu : 381.58 MiB

  • Bölmeler :

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

mslr_web/10k_fold2

  • İndirme boyutu : 1.15 GiB

  • Veri kümesi boyutu : 381.58 MiB

  • Bölmeler :

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

mslr_web/10k_fold3

  • İndirme boyutu : 1.15 GiB

  • Veri kümesi boyutu : 381.58 MiB

  • Bölmeler :

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

mslr_web/10k_fold4

  • İndirme boyutu : 1.15 GiB

  • Veri kümesi boyutu : 381.58 MiB

  • Bölmeler :

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

mslr_web/10k_fold5

  • İndirme boyutu : 1.15 GiB

  • Veri kümesi boyutu : 381.58 MiB

  • Bölmeler :

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

mslr_web/30k_fold1

  • İndirme boyutu : 3.59 GiB

  • Veri kümesi boyutu : 1.17 GiB

  • Bölmeler :

Bölmek Örnekler
'test' 6.306
'train' 18.919
'vali' 6.306

mslr_web/30k_fold2

  • İndirme boyutu : 3.59 GiB

  • Veri kümesi boyutu : 1.17 GiB

  • Bölmeler :

Bölmek Örnekler
'test' 6.307
'train' 18.918
'vali' 6.306

mslr_web/30k_fold3

  • İndirme boyutu : 3.59 GiB

  • Veri kümesi boyutu : 1.17 GiB

  • Bölmeler :

Bölmek Örnekler
'test' 6.306
'train' 18.918
'vali' 6.307

mslr_web/30k_fold4

  • İndirme boyutu : 3.59 GiB

  • Veri kümesi boyutu : 1.17 GiB

  • Bölmeler :

Bölmek Örnekler
'test' 6.306
'train' 18.919
'vali' 6.306

mslr_web/30k_fold5

  • İndirme boyutu : 3.59 GiB

  • Veri kümesi boyutu : 1.17 GiB

  • Bölmeler :

Bölmek Örnekler
'test' 6.306
'train' 18.919
'vali' 6.306