Manuals

• 1. Datasets
  • 1.1. Reviews Datasets
  • 1.2. Twitter Sentiment Datasets
  • 1.3. UCI Machine Learning
  • 1.4. LeQua 2022 Datasets
  • 1.5. LeQua 2024 Datasets
  • 1.6. Image Embedding Datasets
  • 1.7. IFCB Plankton dataset
  • 1.8. Adding Custom Datasets
• 2. Evaluation
  • 2.1. Error Measures
  • 2.2. Evaluation Protocols
• 3. Quantification Methods
  • 3.1. Aggregative Methods
  • 3.2. Non-Aggregative Methods
  • 3.3. Composable Methods
  • 3.4. Meta Models
  • 3.5. Quantifiers with Uncertainty Quantification
• 4. Model Selection
  • 4.1. Targeting a Quantification-oriented loss
  • 4.2. Targeting a Classification-oriented loss
• 5. Plotting
  • 5.1. Diagonal Plot
  • 5.2. Quantification bias
  • 5.3. Error by Drift
  • 5.4. Simplex Visualisation
• 6. Protocols
  • 6.1. APP: Artificial-Prevalence Protocol
  • 6.2. UPP: Sampling from the unit-simplex, the Uniform-Prevalence Protocol
  • 6.3. NPP: Natural-Prevalence Protocol
  • 6.4. Dirichlet Protocol
  • 6.5. Other protocols