STAT 4601
Data Mining I (Honours)
Data visualization; knowledge discovery in datasets; unsupervised learning: clustering algorithms; dimension reduction; supervised learning: pattern recognition, smoothing techniques, classification. Computer software will be used.
Prerequisites & course information
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.
Sources
- Course catalogue ↗2026–2027
- STAT 4601A W22 ↗2021