PPT-Special Topics in Educational Data Mining

HUDK5199 Spring term 2013 February 18 2013 Todays Class Classification And then some discussion of features in Excel between end of class and 5pm We will start today and continue in future classes as needed. Whedon. Dr. David Lavery. Fall 2014. PH 308, M 600-900. . . . Click on the screen capture above to go the blog entry.. Joss Does the Comics. Special Topics in Film Studies: Joss . Whedon. . . . Ryan . S.J.d. . Baker. PSLC Summer School 2010. Welcome to the EDM track!. Educational Data Mining. “Educational Data Mining is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from educational settings, and using those methods to better understand students, and the settings which they learn in.” . HUDK5199. Spring term, 2013. March 27, 2013. Today’s Class. Correlation Mining. Causal Data Mining. The Situation. You have 100 variables, and you want to know how . each one correlates . to a. variable of interest. Dr. David Lavery, Fall 2016. Entities and Groups. Special Topics in Popular Culture, Fall 2016. Brotherhood without Banners. Special Topics in Popular Culture, Fall 2016. Children of the Forest. Special Topics in Popular Culture, Fall 2016. Ryan . S.J.d. . Baker. PSLC Summer School 2012. Welcome to the EDM track!. On behalf of the track lead, John Stamper, and all of our colleagues. Educational Data Mining. “Educational Data Mining is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from educational settings, and using those methods to better understand students, and the settings which they learn in.” . HUDK5199. Spring term, 2013. March 27, 2013. Today’s Class. Correlation Mining. Causal Data Mining. The Situation. You have 100 variables, and you want to know how . each one correlates . to a. variable of interest. February 13, 2013. Special Session on Excel. We couldn’t find a time that worked for a majority of you guys and worked for me. So instead, we will start using the time between 4:40pm-5pm to go through Excel, . HUDK5199. Spring term, 2013. March 13, 2013. Today’s Class. Imputation in Prediction. Missing Data. Frequently, when collecting large amounts of data from diverse sources, there are missing values for some data sources. HUDK5199. Spring term, 2013. February 6, . 2013. Today’s Class. Diagnostic Metrics. Accuracy. Accuracy. One of the easiest measures of model goodness is . accuracy. Also called . agreement. , when measuring inter-rater reliability. HUDK5199. Spring term, 2013. January . 28, . 2013. Please Ask Questions. After class, three separate people asked me “what is an algorithm?”. It’s a recipe. Please ask questions if I use terms that are unfamiliar to you. Special Topics in Educational Data Mining HUDK5199 Spring term, 2013 February 25, 2013 Today’s Class Feature Engineering and Distillation - What Special Rules for Today Everyone Votes Everyone Participates Core Methods in Educational Data Mining EDUC691 Spring 2019 Welcome! Administrative Stuff Is everyone signed up for class? If not, and you want to receive credit, please talk to me after class Class Schedule Core Methods in Educational Data Mining EDUC 691 Spring 2019 Assignment BA4 Questions? Comments? Concerns? Association Rule Mining Today’s Class The Land of Inconsistent Terminology Association Rule Mining Course/Research Topics. Material derived from other sources and “Mining Massive Datasets” from:. Jure Leskovec, . Anand. . Rajaraman. , Jeff Ullman . Stanford University. http://www.mmds.org . Fayé A. Briggs, PhD.