Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...

Abstract: With the booming rural economy and the deepening of digital transformation, accurately understanding the behavioral patterns of rural consumers has become a key issue that companies and ...

Cryptography secures communication in banking, messaging, and blockchain. Good algorithms (AES, RSA, ECC, SHA-2/3, ChaCha20) are secure, efficient, and widely trusted. Bad algorithms (DES, MD5, SHA-1, ...

ABSTRACT: This study presents a comparative analysis of machine learning models for threat detection in Internet of Things (IoT) devices using the CICIoT2023 dataset. We evaluate Logistic Regression, ...

In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat 8 remote ...

Abstract: The purpose of this study is to predict obesity using KNN algorithm compared with Random Forest algorithm. This research paper focuses on the creation of a novel method for obesity ...

This is a Machine Learning model developed with "Decision Trees Algorithm" and "Random Forest Algorithm" to predict the turnover of HDFC bank with a given dataset of the previous turnovers and ...

Design and Implementation of Random Forest algorithm from scratch to execute Pacman strategies and actions in a deterministic, fully observable Pacman Environment. This is a Machine Learning model ...