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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.

Multi-format serialization library for C++17: JSON/JSONC, CSV and MsgPack (dependency-free), plus XML and YAML

  • csv
  • json
  • serialization
  • xml

Single-header C++ JIT compiler/evaluator for mathematical expressions

  • expression-evaluator
  • expression-parser
  • formula-engine
  • formula-evaluator