movie_rationales

• Deskripsi :

Kumpulan data dasar pemikiran film berisi alasan beranotasi manusia untuk ulasan film.

• Beranda : http://www.cs.jhu.edu/~ozaidan/rationales/

• Kode sumber : tfds.text.MovieRationales

• Versi :

  • 0.1.0 (default): Tidak ada catatan rilis.

• Ukuran unduhan : 3.72 MiB

• Ukuran dataset : 8.37 MiB

• Di-cache otomatis ( dokumentasi ): Ya

• Perpecahan :

Membelah	Contoh
'test'	199
'train'	1.600
'validation'	200

• Struktur fitur :

FeaturesDict({
    'evidences': Sequence(Text(shape=(), dtype=string)),
    'label': ClassLabel(shape=(), dtype=int64, num_classes=2),
    'review': Text(shape=(), dtype=string),
})

• Dokumentasi fitur :

Fitur	Kelas	Membentuk	Dtype	Keterangan
	fiturDict
bukti	Urutan (Teks)	(Tidak ada,)	rangkaian
label	LabelKelas		int64
tinjauan	Teks		rangkaian

• Kunci yang diawasi (Lihat as_supervised doc ): None

• Gambar ( tfds.show_examples ): Tidak didukung.

• Contoh ( tfds.as_dataframe ):

• Kutipan :

@unpublished{eraser2019,
    title = {ERASER: A Benchmark to Evaluate Rationalized NLP Models},
    author = {Jay DeYoung and Sarthak Jain and Nazneen Fatema Rajani and Eric Lehman and Caiming Xiong and Richard Socher and Byron C. Wallace}
}
@InProceedings{zaidan-eisner-piatko-2008:nips,
  author    =  {Omar F. Zaidan  and  Jason Eisner  and  Christine Piatko},
  title     =  {Machine Learning with Annotator Rationales to Reduce Annotation Cost},
  booktitle =  {Proceedings of the NIPS*2008 Workshop on Cost Sensitive Learning},
  month     =  {December},
  year      =  {2008}
}