Confusion matrix and classification performance metrics generated by the decision tree (Low Purchasing Potential – LPP: 10 and Major Purchasing Potential – MPP: 5). The performance parameters ...

Secondly, the residuals of the previous step are modeled with a decision tree using all the available features ... The module depends on NumPy, SciPy and Scikit-Learn (>=0.24.2). Python 3.6 or above ...

This project is an AI-powered medical diagnosis assistant that identifies pneumonia from chest X-ray images using deep learning. Built with PyTorch and trained on a Kaggle dataset, the model leverages ...

in addition to traditional classification techniques like Logistic Regression, Decision Trees, and Support Vector Machines (SVM). In order to evaluate the effectiveness of these machine learning and ...

Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...

This study applies the Team Data Science Process to the modelling stage, utilizing machine learning algorithms such as Random Forest, XGBoost, and Decision Tree to develop ... The best classification ...