Transcript COMP 4332, RMBI 4330 Advanced Data Mining (Spring 2012) Qiang Yang Hong Kong University of Science and Technology [email protected] http://www.cs.ust.hk 2015/11/6 Course Introduction.

COMP 4332, RMBI 4330
Advanced Data Mining (Spring
2012)
Qiang Yang
Hong Kong University of Science and Technology
[email protected]
http://www.cs.ust.hk
2015/11/6
Course Introduction
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Topics
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Review of Basics
Practical Data Mining
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Imbalanced Data
Streaming and Time Series Data
Big Data
Social Recommendation
Social Media and Social Networks
Hands on: 2 Major Projects
Student Presentations
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Outcome and Objective
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Student will know the current state of
the art in Data Mining
Student will be able to implement a
practical data mining project
Student will be able to present their
ideas well
Prepared for PG study, Internship, etc.
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Projects:
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Project 1:
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KDDCUPs on credit rating and customer
retention (KDDCUP 2009)
Project 2:
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based on KDDCUPs
Yahoo! Music Recommendation (KDDCUP
2011)
Project 3 (Optional): KDDCUP 2012
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KDDCUP Examples
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KDDCUP from past years
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In general, we wish to
2007:
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Predict if a user is going to rate a movie?
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Predict how many users are going to rate a
movie?
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2006:
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Input: Data
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Output:
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Build model
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Apply model to future data
Predict if a patient has cancer from
medical images
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2005:
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Given a web query (“Apple”), predict
the categories (IT, Food)
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1998:
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Given a person, predict if this
person is going to donate money
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Important Sites
 Instructor Web Site
 http://www.cse.ust.hk/~qyang/4332
 TA: Yin Zhu and Kaixiang Mo
 Assignment Hand-in: online
 [email protected]
 Course Discussion Site:
 Check out the web cite…
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Prerequisites
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Statistics and Probability would help,
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Machine Learning/Pattern Recognition would
help,
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But will be reviewed in class
We will review some most important algorithms
One programming language
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We will teach new languages in the tutorial
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Grading
 Assignments 10%
 Course Projects and Presentations: 50%
 Final Exam 40%
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More info
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Textbooks:
 Listed on Course Website
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2015/11/6
Buy them online if you wish
Course Introduction
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