1. Part I Data Mining Fundamentals

2. Data Mining: A First View Chapter 1

3. 1.1 Data Mining: A Definition

4. Data Mining The process of employing one or more computer learning techniques to automatically analyze and extract knowledge from data.

5. Induction-based Learning The process of forming general concept definitions by observing specific examples of concepts to be learned.

6. Knowledge Discovery in Databases (KDD) The application of the scientific method to data mining. Data mining is one step of the KDD process.

7. 1.2 What Can Computers Learn?

8. Four Levels of Learning Facts Concepts Procedures Principles

9. Concepts Computers are good at learning concepts. Concepts are the output of a data mining session.

10. Three Concept Views Classical View Probabilistic View Exemplar View

11. Supervised Learning Build a learner model using data instances of known origin. Use the model to determine the outcome new instances of unknown origin.

12. Supervised Learning: A Decision Tree Example

13. Decision Tree A tree structure where non-terminal nodes represent tests on one or more attributes and terminal nodes reflect decision outcomes.

15. Figure 1.1 A decision tree for the data in Table 1.1

17. Production Rules IF Swollen Glands = Yes THEN Diagnosis = Strep Throat IF Swollen Glands = No & Fever = Yes THEN Diagnosis = Cold IF Swollen Glands = No & Fever = No THEN Diagnosis = Allergy

18. Unsupervised Clustering A data mining method that builds models from data without predefined classes.

20. 1.3 Is Data Mining Appropriate for My Problem?

21. Data Mining or Data Query? Shallow Knowledge Multidimensional Knowledge Hidden Knowledge Deep Knowledge

22. Data Mining vs. Data Query: An Example Use data query if you already almost know what you are looking for. Use data mining to find regularities in data that are not obvious.

23. 1.4 Expert Systems or Data Mining?

24. Expert System A computer program that emulates the problem-solving skills of one or more human experts.

25. Knowledge Engineer A person trained to interact with an expert in order to capture their knowledge.

26. Figure 1.2 Data mining vs. expert systems

27. 1.5 A Simple Data Mining Process Model

28. Figure 1.3 A simple data mining process model

29. Assembling the Data The Data Warehouse Relational Databases and Flat Files

30. Mining the Data Interpreting the Results Result Application

31. 1.7 Data Mining Applications