In online advertising, click-through rate (CTR) is a very important metric for evaluating ad performance. As a result, click prediction systems are essential and widely used for sponsored search and real-time bidding.
For this competition, we have provided 11 days worth of Avazu data to build and test prediction models. Can you find a strategy that beats standard classification algorithms? The winning models from this competition will be released under an open-source license.
train - Training set. 10 days of click-through data, ordered chronologically. Non-clicks and clicks are subsampled according to different strategies. test - Test set. 1 day of ads to for testing your model predictions. sampleSubmission.csv - Sample submission file in the correct format, corresponds to the All-0.5 Benchmark. Data fields
id: ad identifier click: 0/1 for non-click/click hour: format is YYMMDDHH, so 14091123 means 23:00 on Sept. 11, 2014 UTC. C1 -- anonymized categorical variable banner_pos site_id site_domain site_category app_id app_domain app_category device_id device_ip device_model device_type device_conn_type C14-C21 -- anonymized categorical variables
Competition Link : https://www.kaggle.com/c/avazu-ctr-prediction