Supervised Model-based Learning Algorithm

A Supervised Model-based Learning Algorithm is a model-based learning algorithm that can be applied by a supervised model-based learning system to solve a supervised model-based learning task.

• Context:
  • It can range from being a Supervised Model-based Classification Algorithm to being a Supervised Model-based Ranking Algorithm to being a Supervised Model-based Estimation Algorithm.
  • It can range from being a Lazy Supervised Model-based Learning Algorithm to being an Eager Supervised Model-based Learning Algorithm.
  • It can range from being a Discriminative Supervised Learning Algorithm to being a Generative Supervised Learning Algorithm.
• Example(s):
  • a Regression Algorithm, such as a least-squares function fitting algorithm.
  • a Statistical Modeling Algorithm, such as s Linear Model Learning Algorithm or a Logistic Regression Model Learning Algorithm.
  • a Decision Tree Learning Algorithm, such as a C4.5 Algorithm.
  • a Discriminative Machine Learning Algorithm, such as a logistic regression.
  • a Neural-Network Learning Algorithm, such as a backprop learning algorithm.
  • a Kernel-based Learning Algorithm, such as an SVM algorithm.
  • …
• Counter-Example(s):
  • an Instance-based Learning Algorithm, such as: k-nearest neighbor algorithm.
  • a Locally Weighted Regression Algorithm.
  • an Unsupervised Model-based Learning Algorithm.
• See: Supervised Instance-based Learning Algorithm.

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