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: Lung cancer is among the leading causes of global mortality, driving the need for safer and more affordable therapeutic alternatives. This study aims to develop a machine learning-based ...

According to Andrej Karpathy on Twitter, the Python random.seed() function produces identical random number generator (RNG) streams when seeded with positive and negative integers of the same ...

ABSTRACT: The study aimed to assess the contamination of four fish species (Heterotis niloticus, Oreochromis niloticus, Parachanna obscura, and Sarotherodon melanotheron) by 24 pesticide residues. A ...

ABSTRACT: Predicting knowledge of tuberculosis (TB) could imply several significant changes in the management, control and prevention of this disease. These would be based on advanced technological ...

Abstract: Random Forest is a well-known type of ensemble learning, which combines a number of decision trees to improve the prediction ability and reduce the risk of overfitting. This paper aims at ...

This project basically aims to provide a visual representation and comparative analysis of close price data related to different company ticker. It involves an interactive dashboard for users to ...

Implemented and compared Random Forest, Decision Tree, KNN, SVM, and Logistic Regression outcomes with a confusion matrix. Concluded that Random Forest achieved the highest accuracy of 85% to predict ...