An Approximation Method for Fitted Random Forests. (arXiv:2207.02184v1 [stat.ML])

Random Forests (RF) is a popular machine learning method for classification
and regression problems. It involves a bagging application to decision tree
models. One of the primary advantages of the Random Forests model is the
reduction in the variance of the forecast. In large scale applications of the
model with millions of data points and hundreds of features, the size of the
fitted objects can get very large and reach the limits on the available space
in production setups, depending …

approximation arxiv ml random random forests