Improving Classifier Generalization Real-Time Machine Learning based Applications /

This book elaborately discusses techniques commonly used to improve generalization performance in classification approaches. The contents highlight methods to improve classification performance in numerous case studies: ranging from datasets of UCI repository to predictive maintenance problems and c...

Deskribapen osoa

Gorde:
Xehetasun bibliografikoak
Egile Nagusiak: Sevakula, Rahul Kumar (Egilea), Verma, Nishchal K. (Egilea)
Erakunde egilea: SpringerLink (Online service)
Formatua: Baliabide elektronikoa eBook
Hizkuntza:ingelesa
Argitaratua: Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Edizioa:1st ed. 2023.
Saila:Studies in Computational Intelligence, 989
Gaiak:
Sarrera elektronikoa:https://doi.org/10.1007/978-981-19-5073-5
Etiketak: Etiketa erantsi
Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!
Aurkibidea:
  • Introduction to classification algorithms
  • Methods to improve generalization performance
  • MVPC – a classifier with very low VC dimension
  • Framework for reliable fault detection with sensor data
  • Membership functions for Fuzzy Support Vector Machine in noisy environment
  • Stacked Denoising Sparse Autoencoder based Fuzzy rule classifiers
  • Epilogue.