Theory and applications for the supervised learning method based on gradient algorithms Part I-Fundamental algorithm

Mathematics

• Supervised Learning 100%
• Gauss-Newton Method 95%
• Gradient Algorithm 85%
• Levenberg-Marquardt Algorithm 84%
• Gradient Method 78%
• Levenberg-Marquardt Method 51%
• Training Algorithm 28%
• Learning Rate 24%
• Local Convergence 19%
• Conjugate Gradient Method 18%
• Training 18%
• Second derivative 18%
• Vary 14%
• Gradient 13%
• Family 8%

Engineering & Materials Science

• Gradient methods 84%
• Newton-Raphson method 77%
• Supervised learning 74%
• Conjugate gradient method 22%
• Derivatives 14%