soft margin svms
people.eecs.berkeley.edu · 2,608 words · saved by 1 readers
N/A
18 Jonathan Richard Shewchuk 4 Soft-Margin Support Vector Machines; Features SOFT-MARGIN SUPPORT VECTOR MACHINES (SVMs) Solves 2 problems: – Hard-margin SVMs fail if data not linearly separable. – ” ” ” sensitive to outliers. 9.2 Support Vector Classifiers 345 3 3 2 2 X2 X2…
related reading
- Support vector machine - Wikipediaen.wikipedia.org
- Support vector machine - Wikipediaen.wikipedia.org
- CS231n Deep Learning for Computer Visioncs231n.github.io
- Kernel methoden.wikipedia.org
- Survey on SVM and their application in image classificationlink.springer.com
- Deep Learning using Linear Support Vector Machinesarxiv.org
- svm_dual_kernelcs.cmu.edu
- Introduction to Support Vector Machines (SVMs)mlarchive.com
- lecture_2.pdfcs231n.stanford.edu
- perceptron learning algo, max margin classifierspeople.eecs.berkeley.edu
- 02.pdfpeople.eecs.berkeley.edu
- Lecture 2.pptxcs231n.stanford.edu