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Abstract: The traditional K-Nearest Neighbor (KNN) algorithm often encounters problems such as weak feature expression ability and poor adaptability to fixed K-values in image classification tasks, ...

Learn the Adagrad optimization algorithm, how it works, and how to implement it from scratch in Python for machine learning models. #Adagrad #Optimization #Python Trump administration looking to sell ...

ABSTRACT: The objective of this work is to determine the true owner of a land—public or private—in the region of Kumasi (Ghana). For this purpose, we applied different machine learning methods to the ...

This project demonstrates how to implement the K-Nearest Neighbors (KNN) algorithm for classification on a customer dataset. The program iterates through different values of k (number of neighbors) ...

This repository contains the code for a K-Nearest Neighbors (KNN) model built to classify customer segments in Türkiye using the teleCust1000T dataset. The project includes data cleaning, ...

Abstract: This paper proposes an improved KNN algorithm to overcome the class overlapping problem when the class distribution is skewed. Different from the conventional KNN algorithm, it not only ...