README.md

metadata

license: bsd-3-clause
dataset_info:
  features:
    - name: cond_exp_y
      dtype: float64
    - name: m1
      dtype: float64
    - name: g1
      dtype: float64
    - name: l1
      dtype: float64
    - name: 'Y'
      dtype: float64
    - name: D_1
      dtype: float64
    - name: carat
      dtype: float64
    - name: depth
      dtype: float64
    - name: table
      dtype: float64
    - name: price
      dtype: float64
    - name: x
      dtype: float64
    - name: 'y'
      dtype: float64
    - name: z
      dtype: float64
    - name: review
      dtype: string
    - name: sentiment
      dtype: string
    - name: image_path
      dtype: string
    - name: label
      dtype: int64
    - name: cut_Good
      dtype: bool
    - name: cut_Ideal
      dtype: bool
    - name: cut_Premium
      dtype: bool
    - name: cut_Very Good
      dtype: bool
    - name: color_E
      dtype: bool
    - name: color_F
      dtype: bool
    - name: color_G
      dtype: bool
    - name: color_H
      dtype: bool
    - name: color_I
      dtype: bool
    - name: color_J
      dtype: bool
    - name: clarity_IF
      dtype: bool
    - name: clarity_SI1
      dtype: bool
    - name: clarity_SI2
      dtype: bool
    - name: clarity_VS1
      dtype: bool
    - name: clarity_VS2
      dtype: bool
    - name: clarity_VVS1
      dtype: bool
    - name: clarity_VVS2
      dtype: bool
    - name: image
      dtype: image
  splits:
    - name: train
      num_bytes: 187509908
      num_examples: 50000
  download_size: 0
  dataset_size: 187509908

Dataset Card

Semi-synthetic dataset with multimodal confounding. The dataset is generated according to the description in DoubleMLDeep: Estimation of Causal Effects with Multimodal Data.

Dataset Details

Dataset Description

The dataset contains the following columns:

Dataset Sources

The dataset is based on the three commonly used datasets:

• Diamonds dataset
• IMDB dataset
• CIFAR-10 dataset

The original citations can be found below.

Uses

The dataset should as a benchmark to compare different causal inference methods for observational data under multimodal confounding.

Dataset Structure

[More Information Needed]

Limitations

As the confounding is generated via original labels, completely removing the confounding might not be possible.

Citation Information

Dataset Citation

If you use the dataset please cite this article:

@article{klaassen2024doublemldeep,
  title={DoubleMLDeep: Estimation of Causal Effects with Multimodal Data},
  author={Klaassen, Sven and Teichert-Kluge, Jan and Bach, Philipp and Chernozhukov, Victor and Spindler, Martin and Vijaykumar, Suhas},
  journal={arXiv preprint arXiv:2402.01785},
  year={2024}
}

Dataset Sources

The three original datasets can be cited via

Diamonds dataset:

@Book{ggplot2_book,
  author = {Hadley Wickham},
  title = {ggplot2: Elegant Graphics for Data Analysis},
  publisher = {Springer-Verlag New York},
  year = {2016},
  isbn = {978-3-319-24277-4},
  url = {https://ggplot2.tidyverse.org},
}

IMDB dataset:

@InProceedings{maas-EtAl:2011:ACL-HLT2011,
  author    = {Maas, Andrew L.  and  Daly, Raymond E.  and  Pham, Peter T.  and  Huang, Dan  and  Ng, Andrew Y.  and  Potts, Christopher},
  title     = {Learning Word Vectors for Sentiment Analysis},
  booktitle = {Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies},
  month     = {June},
  year      = {2011},
  address   = {Portland, Oregon, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {142--150},
  url       = {http://www.aclweb.org/anthology/P11-1015}
}

CIFAR-10 dataset:

@TECHREPORT{Krizhevsky09learningmultiple,
    author = {Alex Krizhevsky},
    title = {Learning multiple layers of features from tiny images},
    institution = {},
    year = {2009}
}

Dataset Card Authors

Sven Klaassen