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Machine Learning Methods

This book provides a comprehensive and systematic introduction to the principal machine learning methods, covering both supervised and unsupervised learning methods. It discusses essential methods of classification and regression in supervised learning, such as decision trees, perceptrons, support v...

Deskribapen osoa

Gorde:
Xehetasun bibliografikoak
Egile nagusia: Li, Hang (Egilea)
Erakunde egilea: SpringerLink (Online service)
Formatua: Baliabide elektronikoa eBook
Hizkuntza:ingelesa
Argitaratua: Singapore : Springer Nature Singapore : Imprint: Springer, 2024.
Edizioa:1st ed. 2024.
Gaiak:
Machine learning.
Machine Learning.
Statistical Learning.
Sarrera elektronikoa:https://doi.org/10.1007/978-981-99-3917-6
Etiketak: Etiketa erantsi
Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!
Aurkibidea:
  • Chapter 1 Introduction to Machine learning and Supervised Learning
  • Chapter 2 Perceptron
  • Chapter 3 K-Nearest-Neighbor
  • Chapter 4 The Naïve Bayes Method
  • Chapter 5 Decision Tree
  • Chapter 6 Logistic Regression and Maximum Entropy Model
  • Chapter 7 Support Vector Machine
  • Chapter 8 Boosting
  • Chapter 9 EM Algorithm and Its Extensions
  • Chapter 10 Hidden Markov Model
  • Chapter 11 Conditional Random Field.

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