Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for data-driven phrase mining and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns.
2.6. Mining Closed Patterns
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Destrezas que aprenderás
Streams, Sequential Pattern Mining, Data Mining Algorithms, Data Mining
Revisiones
AB
Nov 07, 2016
The course is very helpful and brings fascinating insights for projects.
DA
Apr 28, 2017
Great course for beginners without experience in Python programming
De la lección
Module 1
Module 1 consists of two lessons. Lesson 1 covers the general concepts of pattern discovery. This includes the basic concepts of frequent patterns, closed patterns, max-patterns, and association rules. Lesson 2 covers three major approaches for mining frequent patterns. We will learn the downward closure (or Apriori) property of frequent patterns and three major categories of methods for mining frequent patterns: the Apriori algorithm, the method that explores vertical data format, and the pattern-growth approach. We will also discuss how to directly mine the set of closed patterns.
Impartido por:
Jiawei Han
Abel Bliss Professor
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