Types of Machine Learning

 

“Our algorithms find similar patterns of words and phrases across the content submitted by different students and inform us if such matches are high. Pattern Detection, Sir! The program found out the assignments submitted by these four students are very similar. We looked at it and confirmed what the machine found.”

Well, this brings us to the next category of Machine Learning algorithms – “Unsupervised Learning-based Algorithms”. Unlike supervised algorithms, in this case, “labelled” data is not required to train the algorithm i.e. a supervisor is not needed. For example, the text from the assignments was the only data given to the plagiarism detector. No labels. The unsupervised algorithm in play over here employs a clustering technique. Yes, yes. It does exactly what you are thinking - groups together objects which are similar to each other (and less similar to other data). So, the algorithm used by the school automatically puts all four assignments under one cluster - denoting a very high likelihood of plagiarism.

Source: https://www.univ.ai/post/classroom. 

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