Learn about data mining concepts in this university lecture that covers both spectral clustering and frequent item analysis. Begin with a completion of spectral clustering topics before diving into the frequent items problem domain. Explore key concepts including fi-frequent items, epsilon-approximate frequency problems, and frequency estimation challenges. Examine different categories of algorithms with detailed focus on the Majority algorithm and Misra-Gries algorithm for solving frequency-related problems in data streams. Master these fundamental data mining techniques through clear explanations and theoretical foundations presented in this academic setting.
Data Mining: Streaming Algorithms and the Misra-Gries Algorithm - Spring 2023
Overview
Syllabus
Recording start
Announcements
Spectral clustering finish
Frequent items problem intro
Fi-frequent item
Epsilon-aprox. frequent problem
Frequency estimation problem
Categories of algorithms
Majority algorithm
Misra-Gries algorithm
Lecture ends
Taught by
UofU Data Science
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