I have the data 𝑋∈ℝ𝑛×𝑑 with 𝑛=300,000 the number of data and 𝑑=2048 the number of variables. Of the 𝑛 given I only have about 10,000 labels 𝑦∈{0.1}} so for about 290,000 individuals, I don’t know the labels.
Is there a way to create a good classifier?
I think this problem is widely known as weakly or semi-supervised learning. I just can’t find adequate code on GitHub in pytorch , preferably quite simple and understandable.
Thank you in advance