printer friendly pageSTATS 202: Data Mining and Analysis
Data mining is used to discover patterns and relationships in data. Emphasis is on large complex data sets such as those in very large databases or through web mining. Topics: decision trees, association rules, clustering, case based methods, and data visualization. Prereqs: Introductory courses in statistics or probability (e.g.,
Stats 60), linear algebra (e.g.,
Math 51), and computer programming (e.g.,
CS 105).
Terms: Aut, Sum
| Units: 3
Instructors:
Erdmann-Pham, D. (PI)
;
Tran, L. (PI)
;
Chen, Z. (TA)
...
more instructors for STATS 202 »
Instructors:
Erdmann-Pham, D. (PI)
;
Tran, L. (PI)
;
Chen, Z. (TA)
;
GAO, Z. (TA)
;
Gablenz, P. (TA)
;
Hartog, W. (TA)
;
Hu, A. (TA)
;
Jin, Y. (TA)
;
MacKay, M. (TA)
;
Paul, D. (TA)
;
Xie, R. (TA)
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