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XGBoost Parameters Before running XGboost, we must set three types of parameters: general parameters, booster parameters and task parameters. General parameters relates to which booster we are using to do boosting, commonly tree or linear model Booster parameters depends on which booster you have chosen Learning Task parameters that decides on the learning scenario, for example, regression tasks m
Dear users, Thanks for using and supporting cxxnet. Today, we finally make a hard but exciting decision: we decide to deprecate cxxnet and fully move forward to next generation toolkit MXNet. Please check the feature highlights, speed/memory comparation and examples in MXNet. cxxnet developers, 28th, Sep, 2015 Note: We provide a very simple converter to MXNet. Check guide to see whether your model
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