42037 - Data Mining II (MD2) [UPC]

Type: S3 Course
Semester: Fall
ECTS: 6
Teaching Points: 15
Offer: Annual
Responsible Unit: CS-UPC
Responsible: Lluís Belanche
Language: English
Requirements:

GOALS

To introduce the student to the use of standard data mining methodologies;
To provide the student with a wide view in feature selection and extraction techniques;
To present some data mining techniques based on fuzzy systems;
To work the visual exploration of data using visualization techniques;
To discuss some real study cases in data mining.

CONTENTS

1. Data mining current importance
2. Standard methodologies in data mining: CRISP and SEMMA
3. Dimensionality reduction

Feature selection
- Unsupervised methods
- Supervised methods
Feature extraction
- Unsupervised methods
- Supervised methods

4. Fuzzy systems

Fuzzy inductive reasoning

Hybrid fuzzy systems

5. Visual exploration of data

Relevance of visualization in data mining
Advanced techniques in data visualization

6. Study cases in data mining