A demonstration of how to use PyTorch to implement Support Vector Machine with L2 regularizition and multiclass hinge loss
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Updated
Sep 17, 2018 - Python
A demonstration of how to use PyTorch to implement Support Vector Machine with L2 regularizition and multiclass hinge loss
Official project of DiverseSampling (ACMMM2022 Paper)
The goal of this project is to design a classifier to use for sentiment analysis of product reviews. Our training set consists of reviews written by Amazon customers for various food products. The reviews, originally given on a 5 point scale, have been adjusted to a +1 or -1 scale, representing a positive or negative review, respectively.
This Repository consists of the solutions to various tasks of this course offered by MIT on edX
Jittor reimplementation of DiverseSampling (MM22)
VerDisGAN and HorDisGAN which control the variation degrees for generated samples
These are coding assignments and projects for the CS 675 Machine Learning course.
Assignments and Project from NJIT CS 675
• Machine Learning • In this project we focused on comparing a Bayes optimal classifier with neural network models using different methods, including cross-entropy, exponential, and hinge loss functions.
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