Submitted by
Akranth, ME20B100
Sayi Teja, ME20B108
This repo has the code and results for the parallel implementation of Support vector machine algorithm, parallelization is acheived using OPENMP.
- An important property of support vector machines is that the determination of the model parameters corresponds to a convex optimization problem, and so any local solution is also a global optimum
- If there are multiple solutions all of
which classify the training data set exactly, then we should try to find the one that
will give the smallest generalization error
- The support vector machine approaches this problem through the concept of the margin, which is defined to be the smallest distance between the decision boundary and any of the samples
This repo has the code and results for the parallel implementation of Support vector machine algorithm, different libraries are used for parallelization, OPENMP, MPI and OpenACC.
Work was done as part of Parallel Scientific Computing course offered at IIT Madras by Prof Kameswararao Anupindi.