Assessing and improving prediction and classification : theory and algorithms in C++ /

Carry out practical, real-life assessments of the performance of prediction and classification models written in C++. This book discusses techniques for improving the performance of such models by intelligent resampling of training/testing data, combining multiple models into sophisticated committee...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Masters, Timothy (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Apress, [2018]
Temas:
C++ (Computer program language)
Mathematical models.
Data mining.
Models, Theoretical
Data Mining
Computer Science.
Big Data.
Artificial Intelligence (incl. Robotics)
Probability and Statistics in Computer Science.
Statistics, general.
C++ (Langage de programmation)
Modèles mathématiques.
Exploration de données (Informatique)
mathematical models.
Artificial intelligence.
Maths for computer scientists.
Probability & statistics.
Databases.
COMPUTERS > Programming Languages > C++
Data mining
Mathematical models
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • 1. Assessment of Numeric Predictions
  • 2. Assessment of Class Predictions
  • 3. Resampling for Assessing Parameter Estimates
  • 4. Resampling for Assessing Prediction and Classification
  • 5. Miscellaneous Resampling Techniques
  • 6. Combining Numeric Predictions
  • 7. Combining Classification Models
  • 8. Gaiting Methods
  • 9. Information and Entropy
  • References.

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