$\vec{w}h\alpha\mathfrak{t}\;\; \forall\mathbb{R}\varepsilon\ldots$

support vector machines?

Katerina Papagiannouli (HU Berlin)
2019/04/12, 13:00
TU Berlin, at the BMS seminar Room (MA212)
About what?

In this talk, we will introduce Support vector machines (SVMs). SVMs is a supervised learning method for classification. We will discuss about a particularly useful family of hypothesis spaces called Reproducing Kernel Hilbert spaces (RKHS) for non-linear classification. Finally, we will illustrate SVMs algorithm for pattern recognition using IRIS dataset.