Despite all the perks, decision trees can sometimes overfit or struggle with balancing bias and variance. To further explain, overly simplistic trees may exhibit high bias, while overly complex trees ...

This project focuses on the classification of trees in Lidar data using machine learning techniques. The Lidar data is stored in a LAS file format (.laz), containing approximately 9 million points.

Objective: To determine whether classification tree techniques used on survey data collected at enrollment from older adults in a Medicare HMO could predict the likelihood of an individual being in a ...

The objective of this research is to report results from a new ensemble method for vegetation classification that uses deep learning (DL) and machine learning (ML) techniques. Deep learning and ...

Genomic research has grown immensely, leading to a surge in the discovery of genetic variations. Efficient methods are needed to classify these variants based on their functional significance. This ...