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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.

### This project has been merged ESPHelper. Please use https://github.com/ItKindaWorks/ESPHelper ### A port of the ESPHelper library for ESP32 devices

A fast float to string algorithm based on schubfach.

  • ieee754
  • performance
  • printing