Predictive Analytics using R

Location: Universitat Politecnica de Valencia

Editions: Apr 2018, Mar 2019, Apr 2020 (online due to Covid)

Course Web Page: contact Luis Torgo

Course Description

The main goal of this short course is to provide hands-on experience on key predictive analytics methods using the R environment. The main focus of the short course will be on regression methods (i.e. numeric prediction).

R is currently one of the most used data mining tools witnessing widespread acceptance both in academia and industry. One of the reasons for this success lies on the huge amount of tools and methods that users can access freely. In this short course we will illustrate some of these methods using a hands-on approach.

After taking this course you should be able to use R for:

1. Master frequently used predictive modeling techniques. Data can be modeled in many different ways. The outcomes of these models can provide useful information for decision makers. We will address several concrete modeling tasks with frequently used techniques. We will learn how to obtain and apply these models in R.

2. Correctly assess the performance of models. Performance assessment is a key step for taking advantage of the results of data mining models. Being able to carry out this task in a reliable way is of key importance to make sure future deployment of data mining pays off.