Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

This study investigates the efficency of linear discriminant analysis (LDA) and principal component analysis (PCA) as dimensionality reduction methods to enhance machine learning performance and ...

This project applies unsupervised learning techniques to explore the structure of a dataset using Principal Component Analysis and K Means clustering. The goal is to identify meaningful patterns ...

The Machine Learning-Based Food Image Classification and Calorie Estimation System is an intelligent solution developed to classify food items from images and estimate their corresponding calorie ...