The existing typical clustering algorithms do not perform well on multi-density data. A semi-supervised clustering algorithm for multi-density dataset SCMD is proposed. The pairwise constraints: ...

the goal is to learn a classifier function using a completely labeled dataset. Semi-supervised learning modifies the learning algorithm function allowing the use of partially labeled data.

Compared with traditional classifiers, semi-supervised ... For example, if one has access to unlabeled sequence data the following tricks can be used. The trick is to take advantage of the physical ...

In this challenge, I performed a semi-supervised learning ... again with new training dataset. The results of these experiments are listed in Results section. We can see the classification accuracy ...

Semi-supervised learning is also applicable to real-world problems where a small amount of labeled data would prevent supervised learning algorithms from functioning. For example, it can alleviate ...