STA465
Download as PDF
Introduction to High Dimensional Data Analysis
Subject
STA
Catalog Number
465
Title
Introduction to High Dimensional Data Analysis
Course Description
Geometry of high dimensional data sets. Linear dimension reduction, principal component analysis, kernel methods. Nonlinear dimension reduction, manifold models. Graphs. Random walks on graphs, diffusions, page rank. Clustering, classification and regression in high-dimensions. Sparsity. Computational aspects, randomized algorithms. Prerequisite: Mathematics 218 or 221.
Grading Basis
Graded
Consent (Permission Number)
No Special Consent Required
Min Units
1
Max Units
1
Lecture
Crosslisted Courses
General Education Curriculum Codes
(QS) Quantitative Studies