Materials for the "Minería de datos" subject in the UPM.
Python:
- Feature Subset Selection. Filter and Wrapper approaches.
- KNN.
- Logistic Regression. Some interesting plots are provided.
- Naive Bayes.
R:
- Naive Bayes and Tree-augmented Naive Bayes. Using bnlearn
- Logistic regression.
- KNN.
- Feature Subset selection. Filter and Wrapper approaches.
WEKA:
- Some .arff datasets for explanation.
The students are then expected to find a dataset and apply all the classification models learnt in the lessonss and perform a comparative of the behaviour of this algorithms.
To transform CSV datasets to .arff files you can use several webpages or python scripts. Here is one of them: https://ikuz.eu/csv2arff/
SOME datasets: