I have been really enjoying AutoML to understand the performance of a nice group of models. I made some changes so I could apply exact training and test sets from models I am also looking at outside of KNIME. Another addition I made was to add SVM to the other 9 models which are inside of AutoML.
I am finding that the runtime of the SVM learner is much longer than any other of the models even the neural models which I’m using Tensorflow and Keras cpu environments. For context the other models are running hours 2-4 and the SVM is running days for the same 4 train validation rounds. The input is classification for potency (0,1) and 40K rows of 1024 bitvectors from a morgan fingerprint.
Any experiences or ideas on how I can get comparable performance to the other models?
Thanks in advance!