WEEK 4 - FYP I : RESEARCH OF KNN AND YOLOv8

 Date   : 17.11.2023

Venue :

Time   : 3:00 - 5:00 pm

Activity:

For the week 4 i decide to do a research about the KNN and YOLOv8 to determine the best method to use for my project and make a comparison about the KNN and YOLOv8. 

Objective:

i. Learn the KNN.

ii. Learn the YOLOv8

Content :

Figure 1 : Comparison KNN and YOLOv8.

I found out that KNN is more suitable for me to this project. The accurancy of knn is higher than the yolov8 and its better for doing collecting data sensor that i will be use in this project.

The k-nearest neighbors algorithm, also known as KNN or k-NN, is a non-parametric, supervised learning classifier, which uses proximity to make classifications or predictions about the grouping of an individual data point. 

Conclusion :

I still in futher study for knn and the algorithm for the knn. I still learning to do a knn algoritm and i decide to do knn fine tree because it can do classification of the dataset.