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Dozierende | Dr. Marjolein Fokkema, Universität Leiden, NL |
Abschluss | Teilnahmebestätigung |
Zielpublikum |
Novice and advanced R users from all professional groups who have basic knowledge in statistics. |
Kosten |
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Kurssprache | Englisch |
Beschreibung |
In this course, a range of tree-based methods like classification and regression trees, bagging, random forests and model-based recursive partitioning will be introduced. Tree-based methods provide state-of-the-art data science tools for decision-making and prediction. In contrast to many other statistical methods, trees are easy to interpret and apply. In addition to methods for individual trees, the course will also cover ensemble methods like random forests, that combine hundreds of individual trees and score among the best-performing prediction methods in many machine learning competitions. Lectures focusing on theory and data-analytic examples will be alternated by practical sessions in which we will apply tree-based methods to real-world datasets. The participants should be familiar with basic statistical concepts and techniques (such as linear regression). Prior experience with R is helpful but not mandatory. For all Zurich R Courses participants should bring their own laptops to the course and will be informed by email in advance which packages they need to install. |
Daten |
Mai 15-16, 2017 |
Nach der Anmeldung erhalten Sie zunächst eine kurze automatische Anmeldebestätigung per Email. Wenn Sie diese Email erhalten haben, sind Sie erfolgreich und verbindlich zum Kurs angemeldet. Die schriftliche Rechnung wird aus administrativen Gründen erst ca. zwei Wochen vor Kursbeginn verschickt. |