Hi everyone, I know that maybe my question has nothing to do with the ones that this forum frequents, but the thing is that I have a job from University on terminology and by the terms they have given us, we are pretty sure that it’s about Machine Learning.
However, my colleagues and I lack so much knowledge on the subject and we find it difficult to relate the terms, with which we must develop an outline, these are the terms:
-Risk function *
-Optimal error *
-Composite outlier*
-Detection
-Nonparametric
-Decentralized detection *
-Multitask linear *
-Regression
Some of these terms we have been able to understand, sadly the ones with the asteriscs are the one that we have more trouble with.
We have been documenting ourselves for a two weeks but we still do not find articles or texts that clearly define these concepts, since most of what we find are graduate works, where they only focus on some parts of Machine Learning. And sadly, we do not have much time because on top of this, we are in our final exams…but we are really trying our best with this project.
We would appreciate it if you could give us some details about these terms or how they can be related to each other, even a little info about them would be awesome!
Thank you very much,
Jennifer.
we have to do terminology documentation work and relate these terms to make an outline