Commit 3b28fe37 authored by Gabriele Cavallaro's avatar Gabriele Cavallaro
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Update README.md

parent 4c0b0508
...@@ -53,39 +53,27 @@ Test set: ...@@ -53,39 +53,27 @@ Test set:
- X_test_tile_8_subregion.npy - X_test_tile_8_subregion.npy
- Y_test_tile_8_subregion.npy - Y_test_tile_8_subregion.npy
### Classification with SVM on QA ### Classification with classical SVM (Scikit-Learn)
Follow the instructions of the Jupyter Notebook 👉 experiments/QA_SVM/QA_SVM.py Follow the instructions of the Jupyter Notebook 👉
### Classification with QA-based QSVM (D-Wave QA)
Follow the instructions of the Jupyter Notebook 👉 experiments/QA_SVM/QA_SVM.ipynb
📐 Now you can proceed in two was: ### Classification with Circuit-based QSVM (IBM Quantum Experience)
(1) Follow the instructions of the Jupyter Notebook 👉 run_SVM.ipynb Follow the instructions of the Jupyter Notebook 👉
(2) Make your processing pipeline by using the Python functions: calibrate.py, train.py and test.py. ## Support
(See in the instructions in files)
Have fun!
📬 For any problem, feel free to contact me at g.cavallaro@fz-juelich.de 📬 For any problem, feel free to contact me at g.cavallaro@fz-juelich.de
## Additional Bibliography and Sources
# Quantum_SVM_Algorithms
## Extended Bibliography
P. Rebentrost, M. Mohseni, and S. Lloyd, “Quantum support vector machine for big data classification,” Physical Review Letters, Sep 2014 P. Rebentrost, M. Mohseni, and S. Lloyd, “Quantum support vector machine for big data classification,” Physical Review Letters, Sep 2014
D. Willsch, M. Willsch, H. De Raedt and K. Michielsen, “Support Vector Machines on the D-Wave Quantum Annealer”, 2019
D. Anguita, S. Ridella, F. Rivieccio, R. Zunino, "Quantum optimization for training support vector machines", Neural Networks, 2003 D. Anguita, S. Ridella, F. Rivieccio, R. Zunino, "Quantum optimization for training support vector machines", Neural Networks, 2003
"Implementing QSVM Machine Learning Method on IBM's Quantum Computers", Quantum Computing UK, 2020 "Implementing QSVM Machine Learning Method on IBM's Quantum Computers", Quantum Computing UK, 2020
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