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Discipline Module 3 · Predictive Models

Supervised Learning

Workload
30h
Professor Prof. Dr. Carlos Ferreira PhD in Computer Science from UFMG, with a dual degree from Politecnico di Torino and work focused on predictive models.
Syllabus

Linear models for regression and classification. Logistic regression. Evaluation of predictive models. Naive Bayes model. Tree-based models. Additive models (ensembles). Support Vector Machines. Kernel trick.

Content
  • Linear models for regression and classification
  • Logistic regression
  • Evaluation of predictive models
  • Naive Bayes model
  • Tree-based models
  • Additive models (ensembles)
  • Support Vector Machines
  • Kernel trick
Core Bibliography
  • Han, J., Kamber, M.; Pei, J. Data Mining: Concepts and Techniques. Morgan Kaufmann, 2011.
  • Witten, I. H., Frank, E., Hall, M. A. Data Mining: Practical Machine Learning Tools and Techniques. 3a edição Elsevier Science & Technology, 2011.
  • Bishop, C. M. Pattern Recognition and Machine Learning. New York: Springer, 2006.
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