https://wiki.eecs.yorku.ca/course_archive/2020-21/F/6412/ 2026-04-03T22:17:05+00:00 https://wiki.eecs.yorku.ca/course_archive/2020-21/F/6412/ https://wiki.eecs.yorku.ca/course_archive/2020-21/F/6412/_media/wiki:dokuwiki-128.png text/html 2020-10-31T01:57:07+00:00 aan (aan@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2020-21/F/6412/whats_new?rev=1604109427&do=diff What's New? October 30, 2020 Assignment 3 is posted on eClass. Please find it in the Assignments section in eClass. It is due Friday November 13 at 11:00pm, and accounts for 12% of your total mark. October 14, 2020 The list of potential topics for student presentations is posted on text/html 2020-09-08T17:20:07+00:00 aan (aan@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2020-21/F/6412/grading_scheme?rev=1599585607&do=diff Grading Scheme * Assignments (30%) * Course project (30%) * Paper review and presentation (in-class, online)(10%) * Final exam (20%) * Participation (10%) text/html 2020-09-08T17:17:28+00:00 aan (aan@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2020-21/F/6412/textbook?rev=1599585448&do=diff Reference Books No textbook is required for the course. The following are reference books: * Jiawei Han, Micheline Kamber and Jian Pei, Data Mining -- Concepts and Techniques, Morgan Kaufmann, Third Edition, 2011. * Charu C. Aggarwal, Data Mining, The Textbook, Springer, 2015. text/html 2020-09-08T04:03:39+00:00 aan (aan@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2020-21/F/6412/sidebar?rev=1599537819&do=diff * Home * What's New * Textbook * Grading Scheme <!-- * Course Outline * Important Dates * Grades * Assignments * Assignment 1 * Assignment 2 * Assignment 3 --> <!-- * Forums --> <!-- * Contact --> <!-- * Policies --> * Resources <!-- * FAQs --> * Academic Dishonesty text/html 2020-09-08T03:47:15+00:00 aan (aan@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2020-21/F/6412/resources?rev=1599536835&do=diff Resources Useful Online Resources. * Weka * UCI Machine Learning Repository * KDnuggets * KDD Cup Datasets * Data Mining Software, Applications and Tools * Open Source Software and Data Sets * Google Data Set Search Engine * Kaggle text/html 2020-09-08T03:29:49+00:00 aan (aan@undisclosed.example.com) https://wiki.eecs.yorku.ca/course_archive/2020-21/F/6412/start?rev=1599535789&do=diff EECS 6412 - Data Mining Description Data mining or knowledge discovery from databases (KDD) is one of the most active areas of research in computer science. It is at the intersection of AI/machine learning, database systems, statistics, and data visualization. In this course, we will introduce the concepts of data mining and present data mining algorithms and applications. Topics include association rule mining, sequential pattern mining, classification models, and clustering.