Sumários
Introduction to R
4 Outubro 2016, 15:00 • João Marques Silva
This practical covered single and multilayer perceptrons using R packages. In addition, the exercises provided a revision of R programming basics.
Concept learning and tree models
4 Outubro 2016, 13:00 • João Marques Silva
The fourth lecture reviewed the construction of decision trees and covered three main topics. First, we introduced notation and definitions to be used throughout the semester. These include definitions for binary classification, formalization of different ML scenarios, and definitions of coverage plots and curves and associated ROC plots and curves. Second, we continued the study of tree models, by relating learned decision trees with coverage curves. Third, we studied rule models, namely the inference of lists of rules and sets of rules. In addition, we studied two examples of descriptive ML: subgroup discovery and association rules. We also studied frequent itemset mining, to be used for learning association rules.
Introduction to the R Programming Language
27 Setembro 2016, 15:00 • João Marques Silva
The first practical consisted of practicing a number of online tutorials for the R programming language, providing a basic introduction to the language.
Ingredients of Machine Learning
27 Setembro 2016, 13:00 • João Marques Silva
The second lecture provided an overview of essential concepts in machine learning and data mining, including features, tasks and models, supervised/unsupervised learning, predictive and descriptive models, grouping vs. grading. The lecture described common tasks, including classification, regression, clustering and association rule discovery. The lecture also briefly introduced a categorization of models in machine learning, including geometric, probabilistic and logical, and listed models studied in the course: trees, rules, naive Bayes, kNN, linear models, SVMs, Kmeans, GMMs, and association rules. The lecture concluded by formalizing (binary) classification.