Letter-Recognition
This project presents a model which uses attributes of images of four letters in the Roman alphebat- A,B,P,R- to predict which letter a particular image responds to. Hense, this is a multi- class classification problem.
The file Letters.cs contains 3116 observations, each of which corresponds to a certain image of one of the four letters- A,B,P,R.
To warm up, we start by predicting whether or not the letter is "B". Then, we build several models such as baseline model, logistic regression, CART tree, Random Forest, and compare these models' outcomes.
Afterwards,we try to predict the original problem of the most frequent class over all of the classes. I also build several models such as baseline model, LDA, CART tree, bagging, Random Forest, boosting, and compare these models' outcomes as well.
The project is written in R programming language.