Data Mining:
Concepts and
Techniques
, 1
Chapter 8. Classification: Basic
Concepts
◼ Classification: Basic Concepts
◼ Decision Tree Induction
◼ Bayes Classification Methods
◼ Rule-Based Classification
◼ Model Evaluation and Selection
3
,◼ Techniques to Improve Classification Accuracy:
Ensemble Methods
◼ Summary
◼
4
, Supervised vs. Unsupervised Learning
◼ Supervised learning (classification)
◼ Supervision: The training data (observations, measurements,
etc.) are accompanied by labels indicating the class of the
observations
◼ New data is classified based on the training set
◼ Unsupervised learning (clustering)
◼ The class labels of training data is unknown
5
Concepts and
Techniques
, 1
Chapter 8. Classification: Basic
Concepts
◼ Classification: Basic Concepts
◼ Decision Tree Induction
◼ Bayes Classification Methods
◼ Rule-Based Classification
◼ Model Evaluation and Selection
3
,◼ Techniques to Improve Classification Accuracy:
Ensemble Methods
◼ Summary
◼
4
, Supervised vs. Unsupervised Learning
◼ Supervised learning (classification)
◼ Supervision: The training data (observations, measurements,
etc.) are accompanied by labels indicating the class of the
observations
◼ New data is classified based on the training set
◼ Unsupervised learning (clustering)
◼ The class labels of training data is unknown
5