Non-parametric-Classification

Different techniques, Class project (September 2021)

Intro:

In recent years, the amount of data has been growing very rapidly which has allowed various situations where different characteristics allow us grouping data sets into subgroups with some degree of similarity, this is known as classification. This technique is very important because it allows a better organization of the data, as well as being able to identify possible strange cases that may indicate that something is wrong.

Techniques used:

• Robust LDA
• Logistic regression with ridge kernell
• SVM with RBF and lineal kernells
• K-means and decision trees