EMIS/CSE 8331: Data Mining,
Spring 2015
> Course syllabus
Course Description
This second course in data mining focuses on
understanding the research methods used in the field of data mining.
The course targets students who want to gain in-dept knowledge
about a particular data mining topic
(e.g., PhD students who plan to use a data mining component in their research).
Prerequisites: Successful completion an
introductory data mining course like EMIS 7332/CSE 7331.
It is
assumed that every student is familiar with all the basic data mining topics
(clustering, classification, and association rules) and has some experience
with programming and one or more data mining tools (R, RapidMiner, SAS, SPSS,
Weka, XLMiner, etc.).
Enrolling in this course requires department/instructor consent.
Project Presentation Video
Tutorial Topics
| Date |
Presenter |
Tutorial |
Abstract |
Additional material (code, software, etc.) |
| 1/27 |
Michael Hahsler |
Data Stream Mining |
|
R package stream,
MOA,
Apache Storm,
Apache Samza,
Apache SAMOA,
IBM InfoSphere Streams,
MS StreamInsight
|
| 2/9 |
Jake Drew |
Biological Sequence Classification
|
abstract |
BiostringsTools |
| 2/9 |
Pamprapai Thainiam |
Churn Prediction with Support Vector Machines |
abstract |
|
| 2/16 |
Sri Surya Nulu |
Opinion Mining
|
abstract |
|
| 2/16 |
Chatchai Wangwiwattana |
Data Mining with Outliers: RANSAC |
abstract |
Robust statistics (R),
RANSAC (Python)
|
2/23 2/25 |
Raymond Martin |
Pattern Mining in Streams |
abstract |
|
2/23 2/25 |
Joseph Kasonde |
Ensemble Classification |
abstract |
R examples |
| 2/25 (Wed) |
Sheila Lincoln |
Bayesian Networks |
abstract |
|
| 3/2 |
Taghreed Alghamadi and Ali Almadan |
Energy Load Mining: Time series analysis |
abstract |
ARIMA Models in R (YouTube) |
| 3/16 |
Chris Ayala |
Social Network Mining |
abstract |
Gephi,
Cytoscape
|
| 3/16 |
Richard Ernst |
Name Disambiguation |
abstract |
|
| 3/23 |
Josh Smitherman |
Latent Dirichlet Allocation (LDA) |
abstract |
Code
|
| 3/30 |
Hala El-Ali |
Big Data Technologies |
abstract |
|
| 4/6 |
Tao Shan |
Item-based Collaborative Filtering |
abstract |
|
| 4/6 |
Marie Vasek |
Web-based Malware Detection |
|
|
| 4/13 |
Austin Rosel |
Artificial Neural Networks -
video |
abstract |
R examples |
Michael Hahsler
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