Blikat dobrodružství zachránit a training algorithm for optimal margin classifiers Lízat Tochi strom papír
Support vector machine - Wikipedia
Influence of Varying Training Set Composition and Size on Support Vector Machine-Based Prediction of Active Compounds | Journal of Chemical Information and Modeling
PDF] A training algorithm for optimal margin classifiers by Bernhard E. Boser, Isabelle Guyon, Vladimir Vapnik · 10.1145/130385.130401 · OA.mg
Introduction to Support Vector Machines - ppt download
Support Vector Machine (SVM) Algorithm - Javatpoint
A Comparative Study of Training Algorithms for Supervised Machine Learning | Semantic Scholar
Which machine learning algorithm should I use? - The SAS Data Science Blog
Machine Learning and Credit Risk (part 4) - Support vector Machines - Analytics R Us(ers)
Efficient Kernel Selection - ppt download
Support Vector Machine | Encyclopedia MDPI
Guide to Support Vector Machine (SVM) Algorithm
PDF] Using SVM to pre-classify government purchases | Semantic Scholar
Support Vector Machines for Binary Classification - MATLAB & Simulink
Support Vector Machines for Beginners - Linear SVM - A Developer Diary
PDF) A Training Algorithm for Optimal Margin Classifier
Support Vector Machine (SVM). Support Vector Machine algorithm… | by Vivek Salunkhe | Medium
Demystifying Maths of SVM — Part 1 | by Krishna Kumar Mahto | Towards Data Science
Entropy | Free Full-Text | Toward Accelerated Training of Parallel Support Vector Machines Based on Voronoi Diagrams
10.1 Maximal Margin Classifier | My Data Science Notes
Margin (machine learning) - Wikipedia
Recent advances and applications of machine learning in solid-state materials science | npj Computational Materials
Machine Learning Algorithms Explained: Support Vector Machine - StrataScratch
Gabriel Peyré on Twitter: "Oldies but goldies: B. Boser, I. Guyon, V. Vapnik, A Training Algorithm for Optimal Margin Classifiers, 1992. Introduced kernel SVM for non-parametric classification. https://t.co/kcR0unUgw0 https://t.co/qPijvbK6D7" / Twitter