Difference between revisions of "Boosting"

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[https://www.google.com/search?q=Gradient+Boosting+Algorithms+machine+learning+ML+artificial+intelligence ...Google search]
 
[https://www.google.com/search?q=Gradient+Boosting+Algorithms+machine+learning+ML+artificial+intelligence ...Google search]
  
* [[Backpropagation]] ... [[Feed Forward Neural Network (FF or FFNN)|FFNN]] ... [[Forward-Forward]] ... [[Activation Functions]] ... [[Loss]] ... [[Boosting]] ... [[Gradient Descent Optimization & Challenges|Gradient Descent]] ... [[Algorithm Administration#Hyperparameter|Hyperparameter]] ... [[Manifold Hypothesis]] ... [[Principal Component Analysis (PCA)|PCA]]
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* [[Backpropagation]] ... [[Feed Forward Neural Network (FF or FFNN)|FFNN]] ... [[Forward-Forward]] ... [[Activation Functions]] ...[[Softmax]] ... [[Loss]] ... [[Boosting]] ... [[Gradient Descent Optimization & Challenges|Gradient Descent]] ... [[Algorithm Administration#Hyperparameter|Hyperparameter]] ... [[Manifold Hypothesis]] ... [[Principal Component Analysis (PCA)|PCA]]
 
* [[Objective vs. Cost vs. Loss vs. Error Function]]
 
* [[Objective vs. Cost vs. Loss vs. Error Function]]
 
* [[Overfitting Challenge]]
 
* [[Overfitting Challenge]]

Revision as of 02:04, 11 July 2023

Youtube search... ...Google search

  1. Regularization
  2. Boosting
  3. Multiclassifiers; Ensembles and Hybrids; Bagging, Boosting, and Stacking


Gradient Boosting Algorithm uses multiple weak algorithms to create a more powerful accurate algorithm. Instead of using a single estimator, having multiple will create a more stable and robust algorithm. The specialty of Gradient Boosting Algorithms is their higher accuracy. There are several Gradient Boosting Algorithms. 10 Machine Learning Algorithms You need to Know | Sidath Asir @ Medium