Learning bounds via sample width for classifiers on finite metric spaces

Keyphrases

• Sample Space 100%
• Finite Metric Space 100%
• Learning Bound 100%
• Generalization Error Bound 25%
• Set Covering 25%
• Generalization Error 25%
• Binary Classification 25%
• Learning Problems 25%
• Metric Space 25%
• Binary Function 25%
• Maximal Width 25%
• Theoretical Computer Science 25%
• Domination number 25%

Mathematics

• Finite Metric Space 100%
• Error Bound 50%
• Metric Space 50%
• Apply It 50%
• Real Line 50%
• domination number γ 50%