thomann
* PostDoc in Machine Learning, * PhD in Probability Theory * Managing Consultant in Data Science
D ONE
thomann's Stars
thomann/plotAR
Walk Through your Data in AR or VR
spark-dataprocessing/spark-dataprocessing
liquidSVM/liquidSVM
Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.