Trained Classification Structure

A Trained Classification Structure is a predictive classification structure produced by a supervised classification system.

• AKA: Induced Classifier, Learned Classification Model Instance.
• Context:
  • It can be produced by a Data-Driven Classification System (that solves a classification model training task)
  • It can range from being a Score-based Classification Function to being a Probabilistic Classification Function.
  • It can range from being a Trained Binary Classifier to being a Trained n-Ary Classifier.
  • It can (typically) be a Software-based Prediction Function.
• Example(s):
  • a Trained Logistic Regression Classifier.
  • a Trained Decision Tree Classifier.
  • a Trained SVM Classifier.
  • a Trained Naive Bayes Classifier.
  • a Trained Neural Network-based Classifier.
  • …
• Counter-Example(s):
  • a Learned Ranking Function.
  • a Learned Point Estimation Function.
• See: Classifier Evaluation Task.

---