Basic description of this course
This course is part of a full series of statistics classes, organized by Genotoul - Biostatistics in the INRA of Toulouse during the years 2011 and 2012. Its aim is to introduce forecasting methods coming from machine learning. It is divided into
- a presentation of the topic (approximately 3 hours);
- practical applications using the free statistical software environment R .
The course is organized as follows:
- basic introduction to machine learning;
- introduction to multilayer perceptrons (neural networks);
- introduction to classification and regression trees (CART algorithm);
- introduction to random forests.
The following R packages are used in the applications:
- car (usefull tools);
- nnet (neural networks);
- e1071 (machine learning);
- rpart (classification and regression trees);
- randomForest (random forests).
How to use the material?
Once all the files have been downloaded, the best way to use them is to make the following directory hierarchy:
- a folder named data containing the data (Rdata and csv files above);
- a folder named ML containing two subdirectories:
- one named Cours with the theoretical part slides;
- one named TP with the slides and the R script related to the practical application.