A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
Hi guys
I was running random forest using spark in R
Can any one tell me how I get accuracy
I would have got normall r square but it drops certain row when random forest runs
so to get r square I need equal rows in original data and predicted data