Avazu_x1

Dataset description:

This dataset contains about 10 days of labeled click-through data on mobile advertisements. It has 22 feature fields including user features and advertisement attributes. The preprocessed data are randomly split into 7:1:2* as the training set, validation set, and test set, respectively.

The dataset statistics are summarized as follows:

Dataset Total #Train #Validation #Test

Avazu_x1 40,428,967 28,300,276 4,042,897 8,085,794
Source: https://www.kaggle.com/c/avazu-ctr-prediction/data
Download: https://huggingface.co/datasets/reczoo/Avazu_x1/tree/main
Repository: https://github.com/reczoo/Datasets
Used by papers:
- Weiyu Cheng, Yanyan Shen, Linpeng Huang. Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions. In AAAI 2020.
- Kelong Mao, Jieming Zhu, Liangcai Su, Guohao Cai, Yuru Li, Zhenhua Dong. FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction. In AAAI 2023.
- Jieming Zhu, Qinglin Jia, Guohao Cai, Quanyu Dai, Jingjie Li, Zhenhua Dong, Ruiming Tang, Rui Zhang. FINAL: Factorized Interaction Layer for CTR Prediction. In SIGIR 2023.

Dataset	Total	#Train	#Validation	#Test
Avazu_x1	40,428,967	28,300,276	4,042,897	8,085,794

Check the md5sum for data integrity:

$ md5sum train.csv valid.csv test.csv
f1114a07aea9e996842c71648e0f6395  train.csv
d9568f246357d156c4b8030fadb8b623  valid.csv
9e2fe9c48705c9315ae7a0953eb57acf  test.csv