DATA MINING

Second cycle degree in COMPUTER SCIENCE

Campus: PADOVA

Language: English

Teaching period: Second Semester

Lecturer: ANNAMARIA GUOLO

Number of ECTS credits allocated: 6


Syllabus
Prerequisites: Basic knowledge of computer science, Databases
Examination methods: Written examination / Practice
Course unit contents: - Introduction to the course: Data analysis as a tool for decision support. Motivations and context for data mining.
- Linear and generalised linear predictive models
- Classification methods: logistic regression, linear discriminant analysis and extensions
- Cross validation
- Model selection and regularisation
- Nonlinear models: semi-parametric and non-parametric regression
- Tree-based methods