https://www.kaggle.com/competitions/avazu-ctr-prediction/overview

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.

• 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

Metrics Log Loss

• Private Score 0.43543

• Public Score 0.43718