Programming language: Python 3.7. Tested on operating systems: Windows 10, CentOS 7.7.1908
The Jupyter notebook HP_single_exp.ipynb contains a simple example code for our hyperbolic perceptron algorithms, hyperbolic perceptron from Weber et al. and Euclidean perceptron on synthetic data with visualization.
python Synthetic_exp.py --savepath [your saving path]
The experimental setting that can be changed are listed as follows:
--N: Number of points (default: 100000)
--d: Dimension (default: 2)
--gamma: Margin (default: 0.01)
--R: Upper bound of the norm of data points (default: 0.95)
--a: The hyperparameter in the second order perceptron (default: 0)
--thread: Number of threads used for parallelization (default: 20)
--chucksize: Chucksize for parallelization (default: 1)
--Repeat: Number of repeat of experiments (default: 20)
Note that you can comment out some methods that you don't want to test in the file Synthetic_exp.py. We have a more detail instruction in it.
The output will be saved as a (3,5,Repeat) numpy arrany.
First axis: acc, mistakes (for perceptron only), running time.
Second axis: methods. They are our hyperbolic perceptron, our second order hyperbolic perceptron, our hyperbolic SVM, SVM from Cho et al., Euclidean SVM.
TBA
Please contact Chao Pan ([email protected]), Eli Chien ([email protected]) if you have any question.