Python implementation of ELM - with optimized speed on MKL-based platforms; Described in conference paper: Radu Dogaru, Ioana Dogaru, "Optimization of extreme learning machines for big data applications using Python", COMM-2018 https://ieeexplore.ieee.org/document/8484265
ADVANTAGES:
- allows quantization of input layer weights (in many cases 2 bits are enough)
- allows quantization of output layer weights (in many cases 8 bits are enough)
- gives very good accuracies with tip=3 (absolute value) hidden layer Well suited for HW and other rezource-constrained machine learning implementations
NOTE: A much faster version with GPU support via CUPY library is available here: https://github.com/radu-dogaru/LB-CNN-compact-and-fast-binary-including-very-fast-ELM
Run directly in Google Colab:
