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๐คฐ๐ฝ make ๐คฐ๐ฟ build ๐คฐ๐ป brain
Use PSVM to classify a ML data set. PSVM only supports binary classification, so the iris data set should either be modified or another data set should be chosen.
Check in some reference code for libSVM to reproduce with a Chapel interface.
If this package is going to expand beyond SVMs, I'd be interested in contributing pseudocode, maybe some prototypes and snarky remarks.
I am currently developing a lame prototype for "Modified Adsorption", a Graph-Based Semi-Supervised Learning routine provided on page 93 of this presentation
If this is interesting, I may also be able to provide some developer resources. I'd be happy to type up the algorithm in a Jupyter Notebook. Please let me know what you think.
The PSVM paper, https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/34638.pdf, may use linear algebra operations or algorithms that are not currently implemented in Chapel. We should list every required operation and algorithm to compare with what Chapel supports now.
Port python examples to Chapel using the svm.chpl
module.
simple_svm_classification.py
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