Data visualization; knowledge discovery in datasets; unsupervised learning: clustering algorithms; dimension reduction; supervised learning: pattern recognition, smoothing techniques, classification. Computer software will be used. Prerequisite(s): STAT 3553 or STAT 3503 or MATH 3806, or permission of the School.Lectures three hours a week, laboratory one hour a week.
Data visualization; knowledge discovery in datasets; unsupervised learning: clustering algorithms; dimension reduction; supervised learning: pattern recognition, smoothing techniques, classification. Computer software will be used. Prerequisite(s): STAT 3553 or STAT 3503 or MATH 3806, or permission of the School.Lectures three hours a week, laboratory one hour a week.