raamana / kernelmethods Goto Github PK

straight forward implementation of __add__, __mul__, __sub__ etc for the KernelMatrix class, with some smart optimizations when possible.

so far only full/dense arrays were tested thoroughly. Deeper/broader testing for sparse arrays would be helpful. This is not expected to take much time.

• kernelmethods version:
• Python version:
• Operating System:

Description

I am using kernelset for multi-core learning. How should I add test set data to kernelset and apply the learned weight data

What I Did

Paste the command(s) you ran and the output.
If there was a crash, please include the traceback here.

this profiling can help find bottlenecks and improve implementation with better internal efficiencies

there is existing work on parallelizing KM computation for large N: #3. It needs to be studied thoroughly for computational and storage efficiencies.

Also, if the better internal data structure (other than the current dict) is feasible.