This project was done by Nicolás Chareca, Pablo Carro, Jianliang Chen and Adrián Baquedano.
This was a part of the subject Algorithms in the Computer Science Major in the Public University of Navarre, in which we were prompted to program the KNN Algorithm to predict a topic of our choice.
The bot uses the KNN (K-Nearest-Neighbors algorithm to find the closest K examples that matches the prompted subject.
We were graded as one of the best projects that were presented in this class with a 9.4 out of 10 for the whole team.
This was the given task list to complete this project:
1. Data entry of the problem dataset.
2. Normalization of the values of the numerical attributes of the dataset.
3. Creation of the data structure.
4. Classification of a new example set using K-NN for K=1.
5. Classification of a set of examples for K=1. 6.
6. Classification of a new example using K-NN for K=k.
7. Classification of a set of examples for K=k.
8. Preprocessing of the dataset using Wilson's Algorithm (ENN).
9. Evolution of the hit accuracy as a function of the number of examples and the value of K.
Steps to compile and execute
Compile with:
make
Execute with:
./main.o