wzhe06/SparkCTR
CTR prediction model based on spark(LR, GBDT, DNN)
This project helps online advertisers and marketers predict the likelihood of a user clicking on an ad or recommended product. It takes historical click data and ad features as input, and outputs the predicted click-through rate (CTR) using various models. Digital marketing specialists, ad platform managers, and data scientists working in e-commerce or advertising would use this to optimize ad performance.
924 stars. No commits in the last 6 months.
Use this if you need to compare and evaluate multiple click-through rate prediction models using Apache Spark's machine learning capabilities, without external libraries.
Not ideal if you prefer a solution integrated with other programming languages or deep learning frameworks beyond Spark MLlib.
Stars
924
Forks
259
Language
Scala
License
Apache-2.0
Category
Last pushed
Mar 06, 2020
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