SY09

Data analysis & Data mining

0. Project 0 : Introduction to R

Unsupervised learning :

1. Project 1 : Descriptive statistics, Principal Component Analysis
2. Project 2 : Classical multidimensional scaling, Hierarchical clustering, K-Means Clustering

Supervised learning :

3. Project 3 : Euclidian distance classifier, multiple discriminant analysis, K-Nearest Neighbor, Bayesian decision theory
4. Discriminant analysis (Quadratic, linear), Naive Bayes Classifier, Linear/Logistic regression, Decision trees