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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