Share Description
In this course, you will learn:
- Be able to create a Data Mining workflow for addressing a clustering problem and collecting potentially useful association rules.
- Be able to solve a clustering problem by using the right closeness measure and selecting the "optimal clustering model" (whatever that means).
- Furthermore, you will be able to create a Data Mining pipeline to extract potentially useful association rules. You will study all of this while using the KNIME open source platform, which combines the power and expressiveness of Weka, R, and Java.
Syllabus:
- Introduction to Clustering and Proximity
- Clustering Algorithms
- Clustering Evaluation
- Association Analysis
