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CTR prediction(feature engineering + learning system)

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Luna

It's a project for click-through-rate(CTR) prediction. Luna includes two parts: CTR prediction feature engineering platform MPI-Based learning system

The learning system contains several projects in folder:"src\main\C++", includes: inslookup: Read dataset into memory. QWLQN : Project from MSRA, it's the Orthant-Wise Limited-memory Quasi-Newton trainer, L1/L2 norm for linear regression and logistic regression problem. myLR : Logistic regression with L1/L2 norm based on OWLQN with customized input data structure. myPeval: Evaluate the result and calculate the AUC performance. mpiLR: mpi-based Logistic Regression with L1/L2 norm and customized input format. mpi-peval: distributed AUC calculation based on MPI-cluster. featselect: couple group lasso model for CTR prediction and feature selection. mpi-featselect: mpi-version couple group lasso model. myPeval-featsel: evaluation project for couple group lasso model. mpi-peval-featsel: mpi-version evaluation project for couple group lasso model.

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