Hi, the scikit-learn random forest does not support GPUs. If you want to do image classification using GPU processing, the standard way in this day and age is to use a neural network library like TensorFlow/keras or pytorch. GPUs can be faster than CPUs when the task is SIMD (single instruction multiple data), meaning the same calculation is done many times just on different datapoints. Neural networks are well-suited for such an architecture, decision trees not so much (even though there have been attempts to speed up decision trees using GPUs). So my advice to you depends on how much time you have: If you are willing to invest time to learn about neural networks and the aforementioned libraries, then that is certainly a very valuable skill, especially when looking for a job later on. But if you just need to get your paper done as soon as possible, stick with random forest.
Greetings,Patrick 從我的 Samsung Galaxy 智慧型手機傳送。-------- 原始訊息 --------自： hoang trung Ta <tahoangtr...@gmail.com> 日期： 2018/8/9 02:50 (GMT+01:00) 至： scikit-learn@python.org 主旨： [scikit-learn] Using GPU in scikit learn Dear all members, I am using Random forest for classification satellite images. I have a bunch of images, thus the processing is quite slow. I searched on the Internet and they said that GPU can accelerate the process. I have GPU NDVIA Geforce GTX 1080 Ti installed in the computer Do you know how to use GPU in Scikit learn, I mean the packages to use and sample code that used GPU in random forest classification? Thank you very much -- Ta Hoang Trung (Mr) Master studentGraduate School of Life and Environmental SciencesUniversity of Tsukuba, Japan Mobile: +81 70 3846 2993Email : ta.hoang-trung...@alumni.tsukuba.ac.jp tahoangtr...@gmail.com s1626...@u.tsukuba.ac.jp---- Mapping Technician Department of Surveying and Mapping VietnamNo 2, Dang Thuy Tram street, Hanoi, Viet Nam Mobile: +84 1255151344Email : tahoangtr...@gmail.com
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