Accelerating Random Forest Classification on GPU and FPGA
Milan Shah, Reece Neff, Hancheng Wu, Marco Minutoli, Antonino Tumeo, Michela Becchi · 2022
Random Forests (RFs) are a commonly used machine learning method for classification and regression tasks spanning a variety of application domains, including bioinformatics, business analytics, and software optimization. While prior work has focused primarily on improving performance of the training of RFs, many applications, such as malware identification, cancer prediction, and banking fraud detection, require fast RF classification.