Quantum kernel estimator
Quantum kernel computation skill for quantum machine learningFrom its SKILL.md
npx -y skills add a5c-ai/babysitter --skill quantum-kernel-estimatorAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
SKILL.md
1.5 KB, 189 tokens by cl100k_base, as published. Nobody here has run it
Quantum Kernel Estimator
Purpose
Provides expert guidance on quantum kernel methods for machine learning, enabling kernel-based classifiers and regressors with quantum feature maps.
Capabilities
- Fidelity quantum kernel
- Projected quantum kernel
- Kernel alignment optimization
- Feature map design
- SVM integration with quantum kernels
- Kernel matrix visualization
- Bandwidth tuning
- Trainable kernel circuits
Usage Guidelines
- Feature Map Selection: Design quantum feature map for data encoding
- Kernel Computation: Calculate kernel matrix entries via circuit execution
- Alignment Optimization: Tune kernel for target classification task
- SVM Training: Use quantum kernel with classical SVM solvers
- Performance Evaluation: Assess classification accuracy and quantum advantage
Tools/Libraries
- Qiskit Machine Learning
- PennyLane
- scikit-learn
- CVXPY
- NumPy
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.