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Alternating Decision Tree - Fundamentals and Applications - cover

Alternating Decision Tree - Fundamentals and Applications

Fouad Sabry

Casa editrice: One Billion Knowledgeable

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Sinossi

What Is Alternating Decision Tree
 
A categorization strategy that may be learned by machine learning is known as an alternating decision tree, or ADTree. It is connected to boosting and generalizes decision trees at the same time.
 
How You Will Benefit
 
(I) Insights, and validations about the following topics:
 
Chapter 1: Alternating Decision Tree
 
Chapter 2: Decision Tree Learning
 
Chapter 3: AdaBoost
 
Chapter 4: Random Forest
 
Chapter 5: Gradient Boosting
 
Chapter 6: Propositional Calculus
 
Chapter 7: Support Vector Machine
 
Chapter 8: Method of Analytic Tableaux
 
Chapter 9: Boolean Satisfiability Algorithm Heuristics
 
Chapter 10: Multiplicative Weight Update Method
 
(II) Answering the public top questions about alternating decision tree.
 
(III) Real world examples for the usage of alternating decision tree in many fields.
 
(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of alternating decision tree' technologies.
 
Who This Book Is For
 
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of alternating decision tree.
Disponibile da: 23/06/2023.
Lunghezza di stampa: 205 pagine.

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