# Best Scalable Classification Algorithms

I have a very large data set that I want to perform classification tasks on. There are about 40 million instances, 16 features, and 2 classes.

I'm attempting to use SciKit-learn LinearSVC and LogisticRegression, but after several hours the processes still have not completed.

I have two questions:

1. Is there a way I can estimate the runtime of SciKit-learn classification algorithms? How can I know if the process will complete in minutes, hours, days...?
2. Is there a certain algorithm which can scale exceptionally well for large data sets? Is there a library implementing this?
• Your first question would be off-topic in here (it is about programming in python), while the second one is on-topic. As about guessing the runtime: run it on smaller data samples and interpolate from it to the bigger sample (notice that this does not to have be linear), see e.g. cs.stackexchange.com/questions/192/… – Tim Mar 17 '16 at 8:23
• I'd argue that the time-complexity of various algorithms could be on-topic here too. – Matt Krause Mar 18 '16 at 21:53