wajidarshad/LUPI-SVM
SVM with Learning Using Privileged Information (LUPI) framework
This helps researchers develop more accurate predictive models by leveraging extra 'privileged information' during the training phase. You provide your standard training data along with additional insights that are only available while teaching the model; the output is a more robust model for predictions where that extra insight isn't available. This is ideal for machine learning researchers and data scientists who are building classification systems.
No commits in the last 6 months.
Use this if you have additional, rich information about your training data that isn't available for new, unseen data, and you want to improve your model's prediction accuracy.
Not ideal if you do not have any 'privileged information' to provide during the training phase, or if your primary goal is a standard SVM implementation.
Stars
28
Forks
5
Language
Python
License
GPL-3.0
Category
Last pushed
Nov 16, 2018
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/wajidarshad/LUPI-SVM"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
DannyVanpoucke/LSSVMlib
This repository provides a Python3 Library with implementations of the Least-Squares Support...
lsorber/neo-ls-svm
Neo LS-SVM is a modern Least-Squares Support Vector Machine implementation
AFAgarap/support-vector-machine
An implementation of the L2-SVM for breast cancer detection using the Wisconsin diagnostic dataset.
emirhanai/Classification-thanks-to-the-SVM-model-with-7-years-of-ozone-data-with-Machine-Learning
I developed 2 machine learning software that predict and classify ozone day and non-ozone day....
stabgan/Support-Vector-Regression
I implemented Support Vector Machine as our Regressor both in Python and R