Can I read Indoor Positioning System Classifier Comparison on EtoBox?

Indoor Positioning System Classifier Comparison by MariaDameHutahaean is a document available to read on EtoBox.

What is Indoor Positioning System Classifier Comparison about?

This document summarizes a research paper that compares several classification methods for indoor positioning systems using Wi-Fi signals. The paper uses a dataset collected from 41 locations across 11 buildings on a university campus using a custom Android application. It compares the accuracy of K-Nearest Neighbors (KNN), Naive Bayes, J48 decision tree, and Support Vector Machine (SVM) classifiers using 10-fold cross-validation. The results show that KNN achieved the highest accuracy of 83.58% while SVM h

Author

MariaDameHutahaean

Language

EN