Παρουσίαση/Προβολή

(STAT356) -  ΔΗΜΗΤΡΙΟΣ ΚΑΡΛΗΣ

Περιγραφή Μαθήματος

Α range of statistical and machine learning methods will be described for supervised and unsupervised learning problems. Unsupervised learning: clustering (hierarchical, partition clustering, k-means and its variants, model-based clustering ), data reduction methods. Model Assessment and Selection. Supervised learning:  Methods of Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), k‐nn, decision trees, random forests, SVM, naïve Bayes and others. Cross-validation methods. Statistics for big data problems, new approaches. Regularizations. Statistical methods for networks.   Smoothing approaches in regression.

Ημερομηνία δημιουργίας

Δευτέρα, 19 Φεβρουαρίου 2024